system

Abstract

We provide the system. [Solution] A method for analyzing past application documents and extracting necessary information, Means for obtaining the latest data on applicant information and organizational information from internal or external sources, A means to automatically update application documents based on the latest information obtained, A means of comparing past and new design drawings, extracting the differences, and reflecting those differences in the application documents, A means to finally generate an updated application document with reflected differences and make it accessible via a mobile information terminal, 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 persona chatbot control method performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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 the application procedures to administrative agencies, there is a lot of manual application form creation, and incorrect input and increased labor are problems. Also, it is difficult to appropriately manage applicant information along with changes within an organization such as personnel transfers, and the update of application documents may be delayed. As a result, there is a problem that the efficiency of administrative procedures decreases and time and resources are wasted.

Means for Solving the Problems

[0005] This invention provides a system that analyzes past application documents to automatically extract necessary information and updates applicant and organizational information based on the latest data. Furthermore, by identifying differences in drawings and reflecting them in the application documents, it enables accurate and rapid document creation. In addition, when information changes occur due to personnel changes, it automatically generates a change notification, facilitating the smooth progress of the application process. By using these means, the overall efficiency of application operations is improved, and working time is reduced.

[0006] "Analysis means" refers to a device or software that has the function of automatically extracting necessary information from past application documents.

[0007] "Information acquisition means" refers to devices or software used to acquire the latest data on applicant information and organizational information from internal or external databases.

[0008] "Update means" refers to a device or software that has the function of automatically updating the contents of application documents based on the latest information obtained.

[0009] A "difference reflection means" is a device or software that has the function of comparing past drawings with new drawings, extracting the differences, and appropriately reflecting those differences in the application documents.

[0010] "Generation means" refers to a device or software used to prepare application documents into their final format after updates and differential updates have been applied.

[0011] "Applicant information" refers to information about the individual or organization making the application, including information such as name, contact information, and organization name.

[0012] "Organizational information" refers to information about the organization to which the applicant belongs, including information such as a list of officers and information about positions within the organization.

[0013] A "Change Notification Form" is a document used to formally record and notify changes to applicant information or organizational information. [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] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes 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, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

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

[0019] In the following embodiments, the numbered 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, and the like.

[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 relates to a system for automating and streamlining the application process when installing base stations on properties owned by administrative agencies. This system includes analysis means, information acquisition means, update means, difference reflection means, and generation means.

[0036] Specifically, users upload past application documents and new drawings to the system. Upon receiving this information, the server first uses an analysis tool to extract necessary information from the past application documents. Then, the server uses an information retrieval tool to obtain the latest data on applicant and organizational information from the database.

[0037] Next, the server utilizes update mechanisms to automatically update application documents based on the latest acquired data, reflecting the new information. If there are changes due to personnel changes within the organization, the server automatically generates the appropriate change notification and reflects it as the latest information.

[0038] Furthermore, the server uses a differential reflection mechanism to compare past drawings with new drawings and identify the differences. These differences are automatically reflected in the application documents, ensuring that accurate documents are prepared according to the new installation conditions.

[0039] Finally, the server generates the final application document based on all the information. This generated document is provided to the user and can be downloaded or printed as needed.

[0040] For example, in the case of an application for the installation of a new base station, the user uploads the documents from the previous year, reflects changes in organizational information due to recent organizational reforms, and checks the differences with the newly provided drawings. This allows for the preparation of accurate application documents in a short time, resulting in labor savings and a reduction in errors.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user selects past application documents and new drawing files from their terminal and uploads them to the system.

[0044] Step 2:

[0045] The server receives the uploaded files and uses analysis tools to extract necessary information from past application documents, such as the applicant's name, start date of use, and loan period.

[0046] Step 3:

[0047] The server uses information retrieval methods to access internal databases and obtain the latest information on applicants, the organization's current board of directors, and other relevant data. External databases are also referenced as needed.

[0048] Step 4:

[0049] The server uses an update mechanism to automatically update the contents of past application documents based on the latest information it has obtained, and creates documents that meet the current application requirements.

[0050] Step 5:

[0051] When the server receives information from a user regarding changes such as personnel transfers within the organization, it automatically generates an appropriate change notification form based on that information and adds it to the documents.

[0052] Step 6:

[0053] The server uses a differential update mechanism to compare past drawings with new drawings and extract the changes. The extracted differences are then appropriately reflected in the application documents.

[0054] Step 7:

[0055] The server generates the final application documents, formats them, and then provides the user with a downloadable link. The user reviews the completed documents and submits feedback as needed.

[0056] (Example 1)

[0057] 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."

[0058] Manually updating information in past application documents and ensuring consistency with new drawings during the application process is extremely time-consuming and carries a high risk of human error. In this context, there is a growing need for a system that enables efficient and accurate information updates and differential reflection.

[0059] 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.

[0060] In this invention, the server includes an analysis means, an information acquisition means, an update means, a difference reflection means, and a generation means. This enables the automatic extraction of past document information, acquisition of the latest information, updating of documents, reflection of differences by comparing old and new drawings, and generation of the final document.

[0061] "Analysis means" refers to the techniques and processes for extracting necessary information from historical documents.

[0062] "Information acquisition means" refers to the technology and processes for obtaining the latest information on applicants or organizations from data storage devices or external information sources.

[0063] "Update means" refers to the technology and process that automatically corrects and updates document content based on the latest acquired information.

[0064] "Difference reflection means" refers to the technology and process of comparing past drawings with new drawings, detecting the differences, and reflecting them in the document.

[0065] "Generation method" refers to the technology and process used to create the final document after updates and differential changes have been applied.

[0066] This invention relates to a system for automating and streamlining the application process for providing basic data documents for properties owned by government agencies. The system begins with the user uploading past application documents and new design drawings to the system.

[0067] Specifically, users upload past application documents and new drawing data to a cloud-based system using their devices. The server receives the uploaded data and first extracts necessary information from the past documents using analysis tools. This process utilizes optical character recognition (OCR) technology and natural language processing tools for text analysis. As a result, the contents of the documents are organized as digital information.

[0068] Next, the server uses information retrieval means to obtain the latest information on applicants and organizations from data storage devices, specifically database management systems such as MySQL® or PostgreSQL. The data is retrieved efficiently using SQL queries.

[0069] Based on the latest information obtained, the server utilizes update mechanisms to automatically update documents. A dedicated algorithm is applied to reflect changes in organizational information and assigned personnel in the documents.

[0070] Furthermore, the server uses a difference-reflection mechanism to compare old and new drawings. Utilizing the OpenCV library, it detects differences in the drawings using image processing technology and reflects them in the document. This ensures the creation of accurate documents that reflect changes in installation conditions.

[0071] Ultimately, the generation process produces a document containing all the information. This document, created in PDF or DOCX format, is provided to the user, who can download or print it according to their needs.

[0072] As a concrete example, when applying for the installation of a new base station, the user uploads the application documents from the previous year, and a document reflecting the information updates due to recent organizational reforms and differences in new drawings is quickly generated. This is expected to simplify the procedure and allow it to proceed more efficiently.

[0073] An example of a prompt for the generated AI model would be: "Please describe the automated system that reflects the latest organizational information and drawing changes required for administrative procedures."

[0074] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0075] Step 1:

[0076] The user uploads past application documents and new drawing data to the cloud-based system using a terminal. Input includes past application documents (PDF format) and new design drawings (CAD file format). This data is sent to the system and prepared for processing on the server.

[0077] Step 2:

[0078] When the server receives uploaded past application documents, it uses analysis tools to extract the necessary information. The input is a PDF document, which is converted into text data using optical character recognition (OCR) technology. From the extracted text data, necessary information such as the applicant's name, application details, and date is identified using natural language processing (NLP) and output as structured data.

[0079] Step 3:

[0080] The server uses information retrieval methods to obtain the latest information on applicants and organizations from the database. Input includes extracted applicant IDs and organization codes, which are used to query the MySQL database. Output includes detailed information such as the latest organization name, contact person name, and contact details.

[0081] Step 4:

[0082] The server updates documents using update mechanisms, based on newly acquired latest information. Input consists of past document information and the latest information retrieved from the database; an algorithm is used to apply this information to a text template. The output is an updated document, with data corrected where necessary.

[0083] Step 5:

[0084] The server compares old and new drawings using a differential reflection mechanism. The input consists of past and new drawing data, and image processing is performed using the OpenCV library. Changes in objects and their positions are identified, and differential information is generated as an output, which is then reflected in the document.

[0085] Step 6:

[0086] The server uses a generation mechanism to integrate all information and generate the final application document. The input is a dataset with differential updates and updated information completed, and the document generation engine outputs the final document in PDF or DOCX format. This document is provided to the user and stored in a downloadable format.

[0087] (Application Example 1)

[0088] 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."

[0089] Traditional application procedures in the construction sector have been time-consuming and cumbersome due to the large volume of paperwork and the complexity of update processes. Furthermore, maintaining consistency with past application documents when changes occur is difficult, and manual errors are prone to occur, thus creating a need for efficient and accurate document management. In particular, there is a growing demand for faster procedures at construction sites, and the provision of a system that can meet these needs is essential.

[0090] 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.

[0091] In this invention, the server includes means for analyzing past application documents and extracting necessary information, means for acquiring the latest data on applicant information and organizational information, and means for automatically updating the application documents based on the acquired latest information. This enables users to quickly and accurately access the latest application documents even on-site.

[0092] 1. "Application documents" refer to the documents required for an application, which are generated based on past information and new design plans.

[0093] 2. "Analysis method" refers to a technique that involves investigating past application documents and systematically extracting necessary information.

[0094] 3. "Information acquisition methods" refer to methods for gathering up-to-date data related to the applicant or organization from internal or external sources.

[0095] 4. "Update mechanism" refers to a system that automatically edits and revises existing application documents using the latest acquired information.

[0096] 5. The "difference reflection method" is a procedure that extracts the differences between past and new design drawings and applies those differences to the application document.

[0097] 6. "Generation means" refers to a system that creates the application document in its final form, revised through updates and differential updates, and provides it in digital format.

[0098] 7. A "mobile information terminal" refers to a computer terminal, such as a smartphone or tablet, that allows users to access information while on the move.

[0099] 8. "Personal information" refers to information about individual members within an organization, including details related to personnel changes in particular.

[0100] 9. "Points of concern" refers to opinions and comments that users can use to review the generated application document and request corrections or improvements as needed.

[0101] The system program that realizes this invention primarily generates application documents efficiently through processes of information extraction, data updating, and differential reflection. The server runs a Python-based program to analyze past application documents and extract necessary information. It is designed to be accessible to users via mobile information terminals such as smartphones and tablets.

[0102] The server uses information retrieval means to obtain the latest applicant and organizational information from internal or external sources. Furthermore, the server uses update means to automatically update application documents based on the retrieved data. This update includes the automatic generation of change reports based on changes in personal information.

[0103] Furthermore, the server uses a differential update mechanism to compare past and new design drawings, extract the resulting differences, and reflect them in the application document. This ensures that application documents always contain the latest information.

[0104] As a concrete example, when applying for the installation of a new base station in a construction project, the user uploads last year's documents and new drawings, and the server automatically generates an application document that reflects the latest information. This generated document is then provided to the user via their terminal.

[0105] Specific examples of prompt messages include "Generate project application documents that reflect the latest design drawings" and "Create updated documents that include changes based on past project documents." In this way, the present invention achieves faster and more accurate creation of application documents.

[0106] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0107] Step 1:

[0108] The server receives past application documents and new design drawings uploaded by the user. These files are provided to the analysis system as input data. In this step, necessary information is extracted from the past application documents using text analysis techniques. The extracted information is stored as structured data for use in subsequent processing steps.

[0109] Step 2:

[0110] The server uses information retrieval means to collect the latest information on applicants and organizations from internal or external sources. This process involves searching databases and retrieving the most recent data. This retrieved data is then entered for comparison with historical data, cross-referenced with existing information, and a dataset reflecting the current state is generated.

[0111] Step 3:

[0112] The server utilizes the update mechanism to automatically update the application document using the latest information obtained in Step 2, based on the structured data extracted in Step 1. Specifically, it verifies the consistency of the information and updates the relevant parts of the document if there are any changes. The updated document is output as the latest version containing the new information.

[0113] Step 4:

[0114] The server uses a differential update mechanism to detect differences between past design drawings and newly uploaded design drawings. This comparison process performs graphic analysis to identify changes. The detected differences are automatically reflected in the updated application document and corrected to accurately reflect the installation conditions.

[0115] Step 5:

[0116] Based on the information obtained in steps 3 and 4, the server uses a generation mechanism to create the final application document. The generated document is provided in a format accessible on the user's mobile information terminal, such as a smartphone or tablet. This allows the user to quickly review the application document and provide feedback as needed.

[0117] 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.

[0118] This invention relates to an automated application document generation system incorporating an emotion engine, with the aim of improving the efficiency of administrative application procedures and enhancing the user experience. This system includes analysis means, information acquisition means, update means, difference reflection means, generation means, and an emotion engine.

[0119] Specifically, users upload past application documents and new drawings from their terminals to the system. The server receives these files and automatically extracts the information necessary for the application using analysis tools. Next, the server uses information acquisition tools to retrieve the latest data on applicant and organizational information from internal and external databases, and automatically updates the application documents using update tools.

[0120] Furthermore, the server uses a differential update mechanism to compare the old and new drawings, extract the differences, and reflect them in the application documents. At this point, the emotion engine starts up and recognizes the user's emotions in real time during the application document generation process. If the emotion engine determines, for example, that the user is feeling stressed, it will adjust the interface to simplify operations or display guidance.

[0121] Furthermore, the server records the user's past emotional data and uses that data to personalize the experience of future application procedures. For example, it can improve the user's experience by refining procedures that were previously frustrating. Finally, the server uses a generation method to generate the final application document integrating all the information and provides the user with a download link, enabling accurate and efficient applications.

[0122] In this way, by utilizing an emotion engine, it is possible not only to streamline the application document generation process but also to improve the individual user experience. This system has the significant advantage of providing flexible support that responds to the user's emotions while maintaining the accuracy of the information.

[0123] The following describes the processing flow.

[0124] Step 1:

[0125] The user selects past application documents and new drawing files on their terminal and uploads them to the system.

[0126] Step 2:

[0127] The server receives the uploaded files and uses analysis tools to extract necessary information from the application documents, such as the applicant's name and usage period.

[0128] Step 3:

[0129] The server uses information retrieval methods to obtain applicant and organizational information from the company's latest internal database. If necessary, it also accesses external databases to obtain the latest information on the list of executives.

[0130] Step 4:

[0131] The server utilizes update mechanisms to automatically update application documents using the latest information obtained, correcting them to meet the new requirements.

[0132] Step 5:

[0133] The server uses a differential update mechanism to compare past drawings with new drawings and extract the differences. Based on these differences, it accurately updates the application documents.

[0134] Step 6:

[0135] The server activates an emotion engine to recognize the user's emotions in real time as they interact with the application documents.

[0136] Step 7:

[0137] Based on its emotion engine, the server automatically adjusts the interface and displays guidance according to the user's emotional state. For example, if the user is feeling stressed, it will offer options to simplify the operation.

[0138] Step 8:

[0139] The server generates the final version of the application documents and formats them. This process optimizes the user experience by referencing past sentiment data.

[0140] Step 9:

[0141] The server provides the user with a download link for the generated application documents. The user reviews the final documents and submits feedback as needed.

[0142] Step 10:

[0143] The server stores the received feedback along with sentiment data and uses it to improve future processes. This information is also used to personalize subsequent tasks.

[0144] (Example 2)

[0145] 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".

[0146] In administrative procedures, preparing application documents is time-consuming and laborious, and ensuring accuracy can be difficult. Furthermore, traditional application procedures often lack sufficient support to address user stress and inconvenience. Therefore, there is a need to streamline application processes and improve the user experience.

[0147] 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.

[0148] In this invention, the server includes means for analyzing past application information and extracting necessary data, means for obtaining the latest data on applicants and organizations from internal and external data management devices, and means for recognizing the user's emotions and dynamically adjusting operational support. This enables automatic updating of application information, accurate reflection of differences, and dynamic support tailored to the individual needs of the user.

[0149] "Past application information" refers to data from records and documents previously submitted by the applicant.

[0150] "Analysis" refers to the process of breaking down information, extracting the necessary elements, and organizing them.

[0151] "Latest data" refers to the most up-to-date information currently available, including any significant changes or updates to the application.

[0152] A "data management device" refers to an internal or external system for storing, managing, and retrieving information.

[0153] "Revision" refers to rewriting existing information or documents based on updated content.

[0154] "Difference" refers to a difference that becomes apparent through comparison, and in particular, it indicates inconsistencies between new and old information or data.

[0155] "User" refers to an individual or organization that operates the system and performs various procedures.

[0156] "Recognizing emotions" refers to detecting and analyzing the emotional state of a user.

[0157] "Dynamic adjustment" refers to automatically providing optimal settings and support according to the situation.

[0158] "Application information" refers to a document containing the data and related information necessary for the application procedure.

[0159] This invention is an automated application information generation system aimed at improving the efficiency of administrative application processes and enhancing the user experience. Specifically, this system has the function of analyzing past application information and extracting necessary data. Users upload past application documents and new drawing data to the system using a terminal, and subsequent processing is performed by the server.

[0160] The server first uses OCR (Optical Character Recognition) software as an analysis tool to automatically extract necessary text information from uploaded application documents. This analysis identifies important fields and aggregates them into an internal database. Subsequently, updated applicant and organization information is retrieved from internal or external data management devices using an information retrieval tool. This involves accessing external databases via a REST API to obtain the necessary and up-to-date information.

[0161] Furthermore, the server analyzes the user's emotions in real time during the application process using an emotion recognition engine. If the user is experiencing stress, the server adjusts the interface accordingly, simplifying operations or providing guidance. This emotion analysis utilizes facial recognition software and voice emotion recognition technology.

[0162] Ultimately, the server uses a generative AI model to automatically generate application information that integrates all the data. The generated application information is provided in PDF format for easy download by the user.

[0163] As a concrete example, consider a scenario where a new application for public housing is submitted, and past application documents and new housing plans are uploaded. In this case, the server automatically extracts the necessary data based on the previous application information, updates the applicant and organization information, and generates accurate and efficient new application information.

[0164] An example of a prompt message might be: "I would like to apply for a new municipal housing unit. Please extract the necessary information from my past application documents and the new housing plan, automatically update it, and generate the final application documents. If I become unsure at any point, please display a procedural guide to assist me."

[0165] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0166] Step 1:

[0167] The user selects past application documents and new drawing data from their device and uploads them to the system. The device receives the input data through a file selection dialog and sends it to the server using the HTTP protocol. The input data is stored as a user file, while the output is temporarily stored on the server.

[0168] Step 2:

[0169] The server analyzes the received files. Using OCR (Optical Character Recognition) software, it digitizes the necessary text data contained in the application documents and identifies important fields. The input data is the uploaded image file, and the output is the extracted digitized application information.

[0170] Step 3:

[0171] The server uses information acquisition methods to retrieve the latest applicant and organization information from internal and external data management devices. It accesses external databases using a REST API to retrieve data. The input in this step consists of identified key fields, and the output is the retrieved latest information.

[0172] Step 4:

[0173] The server integrates the extracted data with the latest information and performs automatic updates. Using a document generation library, it modifies the content of application documents based on the latest information and creates new application information. The input is the extracted data and the latest information, and the output is the latest application information.

[0174] Step 5:

[0175] The server uses a differential reflection mechanism to compare the old and new drawings using an image processing algorithm and extract the differences. The difference information is then reflected in the application documents. As a result, the input is the data of the old and new drawings, and the output is updated application information including the differences.

[0176] Step 6:

[0177] The server operates an emotion recognition engine to analyze the user's emotional state in real time. Using facial recognition technology and voice analysis, it adjusts the interface and guidance as needed. Input is real-time image and audio data, and output is the adjusted interface.

[0178] Step 7:

[0179] The server utilizes a generative AI model to generate the final application information, integrating all the necessary data. PDF generation software is used to create the complete application document in PDF format. The input is integrated application data, and the output is the application document in PDF format.

[0180] Step 8:

[0181] The server provides the completed application information to the user. The user can receive a download link from the server and save the file to their device. The input for this step is the generated PDF file, and the output is the application document saved on the user's device.

[0182] (Application Example 2)

[0183] 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".

[0184] In electronic transactions, users often experience emotional burdens, and there is a need to improve the user experience to ensure smooth transaction completion. However, current systems lack interface adjustments and operational support that take user emotions into consideration, hindering the smoothness of transactions. This challenge needs to be addressed.

[0185] 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.

[0186] In this invention, the server includes an analysis means for analyzing past documents and extracting necessary information, an emotion analysis means for detecting the user's emotional state and optimizing the operation procedure based on the detected emotion, and a means for evaluating the user's record state and proposing operation guides or automation of procedures as needed. This enables smoother transactions by providing an optimized interface and individual support according to the user's emotional state.

[0187] "Analysis means" refers to a device or function that analyzes past documents and automatically extracts necessary information.

[0188] "Information acquisition means" refers to a device or function that acquires the latest data on user information or organization information from an internal or external database.

[0189] "Update means" refers to a device or function that automatically updates a document based on the latest information obtained.

[0190] A "difference reflection means" is a device or function that compares past and new records, extracts the differences, and reflects those differences in a document.

[0191] "Generation means" refers to a device or function that ultimately generates a document that has been updated and differentially reflected.

[0192] "Emotional analysis means" refers to a device or function that detects the emotional state of a user and optimizes the operating procedure based on the detected emotions.

[0193] An "operation guide" is a collection of explanations and instructions provided to help users operate the system smoothly.

[0194] "Procedure automation" refers to the process of streamlining operations and procedures performed by users by having a system automatically handle them.

[0195] A description of embodiments for carrying out this invention will be given.

[0196] To realize this application, the system is configured as follows: The server receives past documents provided by the user and extracts the necessary information using analysis tools. Advanced text analysis algorithms are used for the analysis, such as services like Google® Cloud Vision API. This makes it possible to accurately extract user and organization information from documents.

[0197] The analyzed information is retrieved using an information acquisition mechanism to obtain the latest numerical data from internal or external databases. Database technologies such as SQL database management systems are used in this process to ensure accurate data acquisition. Based on the acquired data, an update mechanism automatically updates the document.

[0198] Furthermore, a differential update mechanism compares past documents with new records, extracts differences, and reflects them in the document as much as possible. At this stage, a differential analysis algorithm is used to efficiently process the differences. Finally, a generation mechanism integrates all the information, generates the updated document, and provides it to the user's terminal.

[0199] Furthermore, the system implements emotion analysis capabilities to collect facial and voice data through the user's camera and microphone, and evaluates the user's emotional state in real time. This evaluation is performed using software such as IBM Watson®'s emotion analysis API. Based on the evaluation results, it is possible to adjust the operation guide or suggest automating procedures to improve the user experience.

[0200] For example, if the system detects that a user is experiencing stress during a transaction, it will suggest "batch processing" or "automatic input options." This simplifies the process and provides an environment where the user can continue operating with peace of mind. Another example of an input prompt for the generated AI model might be, "The user seems anxious. How can we make the transaction process easier?"

[0201] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0202] Step 1:

[0203] Users upload past documents from their terminals to the server. The server receives these documents and extracts the necessary information using analysis tools. In this process, the input is the documents provided by the user, and the output is the extracted necessary information. The server then uses a text analysis algorithm to extract user information and organization information to obtain data.

[0204] Step 2:

[0205] The server uses information acquisition methods to collect the latest data based on information obtained from internal and external databases. The input is parsed user information, and the output is an updated set of user information. Here, SQL database queries are used to efficiently obtain the latest relevant information.

[0206] Step 3:

[0207] The server automatically updates documents based on the latest information obtained using the update mechanism. The input is the latest data, and the output is the updated document. The server uses this information to update existing documents by replacing or adding to them.

[0208] Step 4:

[0209] The server uses a differential reflection mechanism to compare past and new records, extract the differences, and reflect them in the document. The input is the past document and the latest analysis data, and the output is an updated document with the differences reflected. Based on the differential analysis algorithm, the server checks the differences and adds or modifies the document.

[0210] Step 5:

[0211] The server generates the final document based on the information integrated by the generation mechanism. The input is the document reflecting the differences, and the output is the final generated document. The server completes the document by integrating all the information while verifying its consistency.

[0212] Step 6:

[0213] The server uses emotion analysis tools to detect the user's emotional state from the user's camera and microphone data. The input is the user's real-time video and audio data, and the output is the emotional state. Here, the IBM Watson emotion analysis API is used to evaluate the user's emotions.

[0214] Step 7:

[0215] The server suggests operation guides and automated procedures based on the user's emotional state. The input is the detected emotional state, and the output is the adjusted or suggested interface or procedure. It provides the user with operation options and suggests efficient procedures through prompts.

[0216] 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.

[0217] Data generation model 58 is a type of 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 those described above. 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 shown 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.

[0218] 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.

[0219] [Second Embodiment]

[0220] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0221] 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.

[0222] 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).

[0223] 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.

[0224] 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.

[0225] 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).

[0226] 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.

[0227] 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.

[0228] 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.

[0229] 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.

[0230] 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.

[0231] 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".

[0232] This invention relates to a system for automating and streamlining the application process when installing base stations on properties owned by administrative agencies. This system includes analysis means, information acquisition means, update means, difference reflection means, and generation means.

[0233] Specifically, users upload past application documents and new drawings to the system. Upon receiving this information, the server first uses an analysis tool to extract necessary information from the past application documents. Then, the server uses an information retrieval tool to obtain the latest data on applicant and organizational information from the database.

[0234] Next, the server utilizes update mechanisms to automatically update application documents based on the latest acquired data, reflecting the new information. If there are changes due to personnel changes within the organization, the server automatically generates the appropriate change notification and reflects it as the latest information.

[0235] Furthermore, the server uses a differential reflection mechanism to compare past drawings with new drawings and identify the differences. These differences are automatically reflected in the application documents, ensuring that accurate documents are prepared according to the new installation conditions.

[0236] Finally, the server generates the final application document based on all the information. This generated document is provided to the user and can be downloaded or printed as needed.

[0237] For example, in the case of an application for the installation of a new base station, the user uploads the documents from the previous year, reflects changes in organizational information due to recent organizational reforms, and checks the differences with the newly provided drawings. This allows for the preparation of accurate application documents in a short time, resulting in labor savings and a reduction in errors.

[0238] The following describes the processing flow.

[0239] Step 1:

[0240] The user selects past application documents and new drawing files from their terminal and uploads them to the system.

[0241] Step 2:

[0242] The server receives the uploaded files and uses analysis tools to extract necessary information from past application documents, such as the applicant's name, start date of use, and loan period.

[0243] Step 3:

[0244] The server uses information retrieval methods to access internal databases and obtain the latest information on applicants, the organization's current board of directors, and other relevant data. External databases are also referenced as needed.

[0245] Step 4:

[0246] The server uses an update mechanism to automatically update the contents of past application documents based on the latest information it has obtained, and creates documents that meet the current application requirements.

[0247] Step 5:

[0248] When the server receives information from a user regarding changes such as personnel transfers within the organization, it automatically generates an appropriate change notification form based on that information and adds it to the documents.

[0249] Step 6:

[0250] The server uses a differential update mechanism to compare past drawings with new drawings and extract the changes. The extracted differences are then appropriately reflected in the application documents.

[0251] Step 7:

[0252] The server generates the final application documents, formats them, and then provides the user with a downloadable link. The user reviews the completed documents and submits feedback as needed.

[0253] (Example 1)

[0254] 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."

[0255] Manually updating information in past application documents and ensuring consistency with new drawings during the application process is extremely time-consuming and carries a high risk of human error. In this context, there is a growing need for a system that enables efficient and accurate information updates and differential reflection.

[0256] 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.

[0257] In this invention, the server includes an analysis means, an information acquisition means, an update means, a difference reflection means, and a generation means. This enables the automatic extraction of past document information, acquisition of the latest information, updating of documents, reflection of differences by comparing old and new drawings, and generation of the final document.

[0258] "Analysis means" refers to the techniques and processes for extracting necessary information from historical documents.

[0259] "Information acquisition means" refers to the technology and processes for obtaining the latest information on applicants or organizations from data storage devices or external information sources.

[0260] "Update means" refers to the technology and process that automatically corrects and updates document content based on the latest acquired information.

[0261] "Difference reflection means" refers to the technology and process of comparing past drawings with new drawings, detecting the differences, and reflecting them in the document.

[0262] "Generation method" refers to the technology and process used to create the final document after updates and differential changes have been applied.

[0263] This invention relates to a system for automating and streamlining the application process for providing basic data documents for properties owned by government agencies. The system begins with the user uploading past application documents and new design drawings to the system.

[0264] Specifically, users upload past application documents and new drawing data to a cloud-based system using their devices. The server receives the uploaded data and first extracts necessary information from the past documents using analysis tools. This process utilizes optical character recognition (OCR) technology and natural language processing tools for text analysis. As a result, the contents of the documents are organized as digital information.

[0265] Next, the server uses information retrieval methods to obtain the latest information on applicants and organizations from data storage devices, specifically database management systems such as MySQL and PostgreSQL. The data is retrieved efficiently using SQL queries.

[0266] Based on the latest information obtained, the server utilizes update mechanisms to automatically update documents. A dedicated algorithm is applied to reflect changes in organizational information and assigned personnel in the documents.

[0267] Furthermore, the server uses a difference-reflection mechanism to compare old and new drawings. Utilizing the OpenCV library, it detects differences in the drawings using image processing technology and reflects them in the document. This ensures the creation of accurate documents that reflect changes in installation conditions.

[0268] Ultimately, the generation process produces a document containing all the information. This document, created in PDF or DOCX format, is provided to the user, who can download or print it according to their needs.

[0269] As a concrete example, when applying for the installation of a new base station, the user uploads the application documents from the previous year, and a document reflecting the information updates due to recent organizational reforms and differences in new drawings is quickly generated. This is expected to simplify the procedure and allow it to proceed more efficiently.

[0270] An example of a prompt for the generated AI model would be: "Please describe the automated system that reflects the latest organizational information and drawing changes required for administrative procedures."

[0271] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0272] Step 1:

[0273] The user uploads past application documents and new drawing data to the cloud-based system using a terminal. Input includes past application documents (PDF format) and new design drawings (CAD file format). This data is sent to the system and prepared for processing on the server.

[0274] Step 2:

[0275] When the server receives uploaded past application documents, it uses analysis tools to extract the necessary information. The input is a PDF document, which is converted into text data using optical character recognition (OCR) technology. From the extracted text data, necessary information such as the applicant's name, application details, and date is identified using natural language processing (NLP) and output as structured data.

[0276] Step 3:

[0277] The server uses information retrieval methods to obtain the latest information on applicants and organizations from the database. Input includes extracted applicant IDs and organization codes, which are used to query the MySQL database. Output includes detailed information such as the latest organization name, contact person name, and contact details.

[0278] Step 4:

[0279] The server updates documents using update mechanisms, based on newly acquired latest information. Input consists of past document information and the latest information retrieved from the database; an algorithm is used to apply this information to a text template. The output is an updated document, with data corrected where necessary.

[0280] Step 5:

[0281] The server compares the old and new drawings using the difference reflection means. The inputs are the past drawing data and the new drawing data, and image processing is performed using the OpenCV library. The changes in objects and the changes in positions are identified, and the difference information listed as output is generated and reflected in the document.

[0282] Step 6:

[0283] The server integrates all the information using the generation means and generates the final application document. The input is the dataset in which the difference reflection and the information update have been completed, and the document generation engine outputs the final document in PDF or DOCX format. This document is provided to the user and stored in a downloadable state.

[0284] (Application Example 1)

[0285] 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".

[0286] The application procedures in the conventional construction field have been time-consuming and laborious due to the large number of documents and the complexity of the update work. Furthermore, when changes occur, it is difficult to maintain consistency with the past application documents, and manual errors are also likely to occur, so efficient and accurate document management is required. In particular, the voices demanding quick procedures at the site are increasing, and it is necessary to provide a system corresponding to this.

[0287] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0288] In this invention, the server includes means for analyzing past application documents and extracting necessary information, means for acquiring the latest data on applicant information and organizational information, and means for automatically updating the application documents based on the acquired latest information. This enables users to quickly and accurately access the latest application documents even on-site.

[0289] 1. "Application documents" refer to the documents required for an application, which are generated based on past information and new design plans.

[0290] 2. "Analysis method" refers to a technique that involves investigating past application documents and systematically extracting necessary information.

[0291] 3. "Information acquisition methods" refer to methods for gathering up-to-date data related to the applicant or organization from internal or external sources.

[0292] 4. "Update mechanism" refers to a system that automatically edits and revises existing application documents using the latest acquired information.

[0293] 5. The "difference reflection method" is a procedure that extracts the differences between past and new design drawings and applies those differences to the application document.

[0294] 6. "Generation means" refers to a system that creates the application document in its final form, revised through updates and differential updates, and provides it in digital format.

[0295] 7. A "mobile information terminal" refers to a computer terminal, such as a smartphone or tablet, that allows users to access information while on the move.

[0296] 8. "Personal information" refers to information about individual members within an organization, including details related to personnel changes in particular.

[0297] 9. "Points of concern" refers to opinions and comments that users can use to review the generated application document and request corrections or improvements as needed.

[0298] The system program that realizes this invention primarily generates application documents efficiently through processes of information extraction, data updating, and differential reflection. The server runs a Python-based program to analyze past application documents and extract necessary information. It is designed to be accessible to users via mobile information terminals such as smartphones and tablets.

[0299] The server uses information retrieval means to obtain the latest applicant and organizational information from internal or external sources. Furthermore, the server uses update means to automatically update application documents based on the retrieved data. This update includes the automatic generation of change reports based on changes in personal information.

[0300] Furthermore, the server uses a differential update mechanism to compare past and new design drawings, extract the resulting differences, and reflect them in the application document. This ensures that application documents always contain the latest information.

[0301] As a concrete example, when applying for the installation of a new base station in a construction project, the user uploads last year's documents and new drawings, and the server automatically generates an application document that reflects the latest information. This generated document is then provided to the user via their terminal.

[0302] Specific examples of prompt messages include "Generate project application documents that reflect the latest design drawings" and "Create updated documents that include changes based on past project documents." In this way, the present invention achieves faster and more accurate creation of application documents.

[0303] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0304] Step 1:

[0305] The server receives the past application documents and new design drawings uploaded by the user. These files are provided to the analysis means as input data. In this step, the necessary information is extracted from the past application documents using text analysis technology. The extracted information is stored as structured data for use in subsequent processing steps.

[0306] Step 2:

[0307] The server uses the information acquisition means to collect the latest information of the applicant and the organization from internal or external information sources. In this process, the database is searched to obtain the latest data. The obtained data is input for comparison with the past data, collated with the existing information, and a dataset reflecting the latest status is generated.

[0308] Step 3:

[0309] The server utilizes the update means and automatically updates the application document using the latest information obtained in Step 2 based on the structured data extracted in Step 1. Specifically, the consistency of the information is confirmed, and if there are changes, the corresponding part of the document is updated. The updated document is output as the latest version containing the new information.

[0310] Step 4:

[0311] The server uses the difference reflection means to detect the differences between the past design drawings and the newly uploaded design drawings. In this comparison process, graphic analysis is performed to identify the points of change. The detected differences are automatically reflected in the updated application document and corrected to the content corresponding to the accurate installation conditions.

[0312] Step 5:

[0313] Based on the information obtained in steps 3 and 4, the server uses a generation mechanism to create the final application document. The generated document is provided in a format accessible on the user's mobile information terminal, such as a smartphone or tablet. This allows the user to quickly review the application document and provide feedback as needed.

[0314] 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.

[0315] This invention relates to an automated application document generation system incorporating an emotion engine, with the aim of improving the efficiency of administrative application procedures and enhancing the user experience. This system includes analysis means, information acquisition means, update means, difference reflection means, generation means, and an emotion engine.

[0316] Specifically, users upload past application documents and new drawings from their terminals to the system. The server receives these files and automatically extracts the information necessary for the application using analysis tools. Next, the server uses information acquisition tools to retrieve the latest data on applicant and organizational information from internal and external databases, and automatically updates the application documents using update tools.

[0317] Furthermore, the server uses a differential update mechanism to compare the old and new drawings, extract the differences, and reflect them in the application documents. At this point, the emotion engine starts up and recognizes the user's emotions in real time during the application document generation process. If the emotion engine determines, for example, that the user is feeling stressed, it will adjust the interface to simplify operations or display guidance.

[0318] Furthermore, the server records the user's past emotional data and uses that data to personalize the experience of future application procedures. For example, it can improve the user's experience by refining procedures that were previously frustrating. Finally, the server uses a generation method to generate the final application document integrating all the information and provides the user with a download link, enabling accurate and efficient applications.

[0319] In this way, by utilizing an emotion engine, it is possible not only to streamline the application document generation process but also to improve the individual user experience. This system has the significant advantage of providing flexible support that responds to the user's emotions while maintaining the accuracy of the information.

[0320] The following describes the processing flow.

[0321] Step 1:

[0322] The user selects past application documents and new drawing files on their terminal and uploads them to the system.

[0323] Step 2:

[0324] The server receives the uploaded files and uses analysis tools to extract necessary information from the application documents, such as the applicant's name and usage period.

[0325] Step 3:

[0326] The server uses information retrieval methods to obtain applicant and organizational information from the company's latest internal database. If necessary, it also accesses external databases to obtain the latest information on the list of executives.

[0327] Step 4:

[0328] The server utilizes update mechanisms to automatically update application documents using the latest information obtained, correcting them to meet the new requirements.

[0329] Step 5:

[0330] The server uses a differential update mechanism to compare past drawings with new drawings and extract the differences. Based on these differences, it accurately updates the application documents.

[0331] Step 6:

[0332] The server activates an emotion engine to recognize the user's emotions in real time as they interact with the application documents.

[0333] Step 7:

[0334] Based on its emotion engine, the server automatically adjusts the interface and displays guidance according to the user's emotional state. For example, if the user is feeling stressed, it will offer options to simplify the operation.

[0335] Step 8:

[0336] The server generates the final version of the application documents and formats them. This process optimizes the user experience by referencing past sentiment data.

[0337] Step 9:

[0338] The server provides the user with a download link for the generated application documents. The user reviews the final documents and submits feedback as needed.

[0339] Step 10:

[0340] The server stores the received feedback along with sentiment data and uses it to improve future processes. This information is also used to personalize subsequent tasks.

[0341] (Example 2)

[0342] 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".

[0343] In administrative procedures, preparing application documents is time-consuming and laborious, and ensuring accuracy can be difficult. Furthermore, traditional application procedures often lack sufficient support to address user stress and inconvenience. Therefore, there is a need to streamline application processes and improve the user experience.

[0344] 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.

[0345] In this invention, the server includes means for analyzing past application information and extracting necessary data, means for obtaining the latest data on applicants and organizations from internal and external data management devices, and means for recognizing the user's emotions and dynamically adjusting operational support. This enables automatic updating of application information, accurate reflection of differences, and dynamic support tailored to the individual needs of the user.

[0346] "Past application information" refers to data from records and documents previously submitted by the applicant.

[0347] "Analysis" refers to the process of breaking down information, extracting the necessary elements, and organizing them.

[0348] "Latest data" refers to the most up-to-date information currently available, including any significant changes or updates to the application.

[0349] A "data management device" refers to an internal or external system for storing, managing, and retrieving information.

[0350] "Revision" refers to rewriting existing information or documents based on updated content.

[0351] "Difference" refers to a difference that becomes apparent through comparison, and in particular, it indicates inconsistencies between new and old information or data.

[0352] "User" refers to an individual or organization that operates the system and performs various procedures.

[0353] "Recognizing emotions" refers to detecting and analyzing the emotional state of a user.

[0354] "Dynamic adjustment" refers to automatically providing optimal settings and support according to the situation.

[0355] "Application information" refers to a document containing the data and related information necessary for the application procedure.

[0356] This invention is an automated application information generation system aimed at improving the efficiency of administrative application processes and enhancing the user experience. Specifically, this system has the function of analyzing past application information and extracting necessary data. Users upload past application documents and new drawing data to the system using a terminal, and subsequent processing is performed by the server.

[0357] The server first uses OCR (Optical Character Recognition) software as an analysis tool to automatically extract necessary text information from uploaded application documents. This analysis identifies important fields and aggregates them into an internal database. Subsequently, updated applicant and organization information is retrieved from internal or external data management devices using an information retrieval tool. This involves accessing external databases via a REST API to obtain the necessary and up-to-date information.

[0358] Furthermore, the server analyzes the user's emotions in real time during the application process using an emotion recognition engine. If the user is experiencing stress, the server adjusts the interface accordingly, simplifying operations or providing guidance. This emotion analysis utilizes facial recognition software and voice emotion recognition technology.

[0359] Ultimately, the server uses a generative AI model to automatically generate application information that integrates all the data. The generated application information is provided in PDF format for easy download by the user.

[0360] As a concrete example, consider a scenario where a new application for public housing is submitted, and past application documents and new housing plans are uploaded. In this case, the server automatically extracts the necessary data based on the previous application information, updates the applicant and organization information, and generates accurate and efficient new application information.

[0361] An example of a prompt message might be: "I would like to apply for a new municipal housing unit. Please extract the necessary information from my past application documents and the new housing plan, automatically update it, and generate the final application documents. If I become unsure at any point, please display a procedural guide to assist me."

[0362] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0363] Step 1:

[0364] The user selects past application documents and new drawing data from their device and uploads them to the system. The device receives the input data through a file selection dialog and sends it to the server using the HTTP protocol. The input data is stored as a user file, while the output is temporarily stored on the server.

[0365] Step 2:

[0366] The server analyzes the received files. Using OCR (Optical Character Recognition) software, it digitizes the necessary text data contained in the application documents and identifies important fields. The input data is the uploaded image file, and the output is the extracted digitized application information.

[0367] Step 3:

[0368] The server uses information acquisition methods to retrieve the latest applicant and organization information from internal and external data management devices. It accesses external databases using a REST API to retrieve data. The input in this step consists of identified key fields, and the output is the retrieved latest information.

[0369] Step 4:

[0370] The server integrates the extracted data with the latest information and performs automatic updates. Using a document generation library, it modifies the content of application documents based on the latest information and creates new application information. The input is the extracted data and the latest information, and the output is the latest application information.

[0371] Step 5:

[0372] The server uses a differential reflection mechanism to compare the old and new drawings using an image processing algorithm and extract the differences. The difference information is then reflected in the application documents. As a result, the input is the data of the old and new drawings, and the output is updated application information including the differences.

[0373] Step 6:

[0374] The server operates an emotion recognition engine to analyze the user's emotional state in real time. Using facial recognition technology and voice analysis, it adjusts the interface and guidance as needed. Input is real-time image and audio data, and output is the adjusted interface.

[0375] Step 7:

[0376] The server utilizes a generative AI model to generate the final application information, integrating all the necessary data. PDF generation software is used to create the complete application document in PDF format. The input is integrated application data, and the output is the application document in PDF format.

[0377] Step 8:

[0378] The server provides the completed application information to the user. The user can receive a download link from the server and save the file to their device. The input for this step is the generated PDF file, and the output is the application document saved on the user's device.

[0379] (Application Example 2)

[0380] 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."

[0381] In electronic transactions, users often experience emotional burdens, and there is a need to improve the user experience to ensure smooth transaction completion. However, current systems lack interface adjustments and operational support that take user emotions into consideration, hindering the smoothness of transactions. This challenge needs to be addressed.

[0382] 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.

[0383] In this invention, the server includes an analysis means for analyzing past documents and extracting necessary information, an emotion analysis means for detecting the user's emotional state and optimizing the operation procedure based on the detected emotion, and a means for evaluating the user's record state and proposing operation guides or automation of procedures as needed. This enables smoother transactions by providing an optimized interface and individual support according to the user's emotional state.

[0384] "Analysis means" refers to a device or function that analyzes past documents and automatically extracts necessary information.

[0385] "Information acquisition means" refers to a device or function that acquires the latest data on user information or organization information from an internal or external database.

[0386] "Update means" refers to a device or function that automatically updates a document based on the latest information obtained.

[0387] A "difference reflection means" is a device or function that compares past and new records, extracts the differences, and reflects those differences in a document.

[0388] "Generation means" refers to a device or function that ultimately generates a document that has been updated and differentially reflected.

[0389] "Emotional analysis means" refers to a device or function that detects the emotional state of a user and optimizes the operating procedure based on the detected emotions.

[0390] An "operation guide" is a collection of explanations and instructions provided to help users operate the system smoothly.

[0391] "Procedure automation" refers to the process of streamlining operations and procedures performed by users by having a system automatically handle them.

[0392] A description of embodiments for carrying out this invention will be given.

[0393] To realize this application, the system is configured as follows: The server receives past documents provided by the user and extracts the necessary information using analysis tools. Advanced text analysis algorithms are used for the analysis, such as services like the Google Cloud Vision API. This makes it possible to accurately extract user and organization information from documents.

[0394] The analyzed information is retrieved using an information acquisition mechanism to obtain the latest numerical data from internal or external databases. Database technologies such as SQL database management systems are used in this process to ensure accurate data acquisition. Based on the acquired data, an update mechanism automatically updates the document.

[0395] Furthermore, a differential update mechanism compares past documents with new records, extracts differences, and reflects them in the document as much as possible. At this stage, a differential analysis algorithm is used to efficiently process the differences. Finally, a generation mechanism integrates all the information, generates the updated document, and provides it to the user's terminal.

[0396] Furthermore, the system implements emotion analysis capabilities to collect facial and voice data through the user's camera and microphone, and evaluates the user's emotional state in real time. This evaluation is performed using software such as IBM Watson's emotion analysis API. Based on the evaluation results, it is possible to adjust the operation guide or suggest automating procedures to improve the user experience.

[0397] For example, if the system detects that a user is experiencing stress during a transaction, it will suggest "batch processing" or "automatic input options." This simplifies the process and provides an environment where the user can continue operating with peace of mind. Another example of an input prompt for the generated AI model might be, "The user seems anxious. How can we make the transaction process easier?"

[0398] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0399] Step 1:

[0400] Users upload past documents from their terminals to the server. The server receives these documents and extracts the necessary information using analysis tools. In this process, the input is the documents provided by the user, and the output is the extracted necessary information. The server then uses a text analysis algorithm to extract user information and organization information to obtain data.

[0401] Step 2:

[0402] The server uses information acquisition methods to collect the latest data based on information obtained from internal and external databases. The input is parsed user information, and the output is an updated set of user information. Here, SQL database queries are used to efficiently obtain the latest relevant information.

[0403] Step 3:

[0404] The server automatically updates documents based on the latest information obtained using the update mechanism. The input is the latest data, and the output is the updated document. The server uses this information to update existing documents by replacing or adding to them.

[0405] Step 4:

[0406] The server uses a differential reflection mechanism to compare past and new records, extract the differences, and reflect them in the document. The input is the past document and the latest analysis data, and the output is an updated document with the differences reflected. Based on the differential analysis algorithm, the server checks the differences and adds or modifies the document.

[0407] Step 5:

[0408] The server generates the final document based on the information integrated by the generation mechanism. The input is the document reflecting the differences, and the output is the final generated document. The server completes the document by integrating all the information while verifying its consistency.

[0409] Step 6:

[0410] The server uses emotion analysis tools to detect the user's emotional state from the user's camera and microphone data. The input is the user's real-time video and audio data, and the output is the emotional state. Here, the IBM Watson emotion analysis API is used to evaluate the user's emotions.

[0411] Step 7:

[0412] The server suggests operation guides and automated procedures based on the user's emotional state. The input is the detected emotional state, and the output is the adjusted or suggested interface or procedure. It provides the user with operation options and suggests efficient procedures through prompts.

[0413] 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.

[0414] 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 those described above. 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 shown 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.

[0415] 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.

[0416] [Third Embodiment]

[0417] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0418] 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.

[0419] 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).

[0420] 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.

[0421] 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.

[0422] 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).

[0423] 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.

[0424] 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.

[0425] 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.

[0426] 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.

[0427] 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.

[0428] 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".

[0429] This invention relates to a system for automating and streamlining the application process when installing base stations on properties owned by administrative agencies. This system includes analysis means, information acquisition means, update means, difference reflection means, and generation means.

[0430] Specifically, users upload past application documents and new drawings to the system. Upon receiving this information, the server first uses an analysis tool to extract necessary information from the past application documents. Then, the server uses an information retrieval tool to obtain the latest data on applicant and organizational information from the database.

[0431] Next, the server utilizes update mechanisms to automatically update application documents based on the latest acquired data, reflecting the new information. If there are changes due to personnel changes within the organization, the server automatically generates the appropriate change notification and reflects it as the latest information.

[0432] Furthermore, the server uses a differential reflection mechanism to compare past drawings with new drawings and identify the differences. These differences are automatically reflected in the application documents, ensuring that accurate documents are prepared according to the new installation conditions.

[0433] Finally, the server generates the final application document based on all the information. This generated document is provided to the user and can be downloaded or printed as needed.

[0434] For example, in the case of an application for the installation of a new base station, the user uploads the documents from the previous year, reflects changes in organizational information due to recent organizational reforms, and checks the differences with the newly provided drawings. This allows for the preparation of accurate application documents in a short time, resulting in labor savings and a reduction in errors.

[0435] The following describes the processing flow.

[0436] Step 1:

[0437] The user selects past application documents and new drawing files from their terminal and uploads them to the system.

[0438] Step 2:

[0439] The server receives the uploaded files and uses analysis tools to extract necessary information from past application documents, such as the applicant's name, start date of use, and loan period.

[0440] Step 3:

[0441] The server uses information retrieval methods to access internal databases and obtain the latest information on applicants, the organization's current board of directors, and other relevant data. External databases are also referenced as needed.

[0442] Step 4:

[0443] The server uses an update mechanism to automatically update the contents of past application documents based on the latest information it has obtained, and creates documents that meet the current application requirements.

[0444] Step 5:

[0445] When the server receives information from a user regarding changes such as personnel transfers within the organization, it automatically generates an appropriate change notification form based on that information and adds it to the documents.

[0446] Step 6:

[0447] The server uses a differential update mechanism to compare past drawings with new drawings and extract the changes. The extracted differences are then appropriately reflected in the application documents.

[0448] Step 7:

[0449] The server generates the final application documents, formats them, and then provides the user with a downloadable link. The user reviews the completed documents and submits feedback as needed.

[0450] (Example 1)

[0451] 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."

[0452] Manually updating information in past application documents and ensuring consistency with new drawings during the application process is extremely time-consuming and carries a high risk of human error. In this context, there is a growing need for a system that enables efficient and accurate information updates and differential reflection.

[0453] 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.

[0454] In this invention, the server includes an analysis means, an information acquisition means, an update means, a difference reflection means, and a generation means. This enables the automatic extraction of past document information, acquisition of the latest information, updating of documents, reflection of differences by comparing old and new drawings, and generation of the final document.

[0455] "Analysis means" refers to the techniques and processes for extracting necessary information from historical documents.

[0456] "Information acquisition means" refers to the technology and processes for obtaining the latest information on applicants or organizations from data storage devices or external information sources.

[0457] "Update means" refers to the technology and process that automatically corrects and updates document content based on the latest acquired information.

[0458] "Difference reflection means" refers to the technology and process of comparing past drawings with new drawings, detecting the differences, and reflecting them in the document.

[0459] "Generation method" refers to the technology and process used to create the final document after updates and differential changes have been applied.

[0460] This invention relates to a system for automating and streamlining the application process for providing basic data documents for properties owned by government agencies. The system begins with the user uploading past application documents and new design drawings to the system.

[0461] Specifically, users upload past application documents and new drawing data to a cloud-based system using their devices. The server receives the uploaded data and first extracts necessary information from the past documents using analysis tools. This process utilizes optical character recognition (OCR) technology and natural language processing tools for text analysis. As a result, the contents of the documents are organized as digital information.

[0462] Next, the server uses information retrieval methods to obtain the latest information on applicants and organizations from data storage devices, specifically database management systems such as MySQL and PostgreSQL. The data is retrieved efficiently using SQL queries.

[0463] Based on the latest information obtained, the server utilizes update mechanisms to automatically update documents. A dedicated algorithm is applied to reflect changes in organizational information and assigned personnel in the documents.

[0464] Furthermore, the server uses a difference-reflection mechanism to compare old and new drawings. Utilizing the OpenCV library, it detects differences in the drawings using image processing technology and reflects them in the document. This ensures the creation of accurate documents that reflect changes in installation conditions.

[0465] Ultimately, the generation process produces a document containing all the information. This document, created in PDF or DOCX format, is provided to the user, who can download or print it according to their needs.

[0466] As a concrete example, when applying for the installation of a new base station, the user uploads the application documents from the previous year, and a document reflecting the information updates due to recent organizational reforms and differences in new drawings is quickly generated. This is expected to simplify the procedure and allow it to proceed more efficiently.

[0467] An example of a prompt for the generated AI model would be: "Please describe the automated system that reflects the latest organizational information and drawing changes required for administrative procedures."

[0468] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0469] Step 1:

[0470] The user uploads past application documents and new drawing data to the cloud-based system using a terminal. Input includes past application documents (PDF format) and new design drawings (CAD file format). This data is sent to the system and prepared for processing on the server.

[0471] Step 2:

[0472] When the server receives uploaded past application documents, it uses analysis tools to extract the necessary information. The input is a PDF document, which is converted into text data using optical character recognition (OCR) technology. From the extracted text data, necessary information such as the applicant's name, application details, and date is identified using natural language processing (NLP) and output as structured data.

[0473] Step 3:

[0474] The server uses information retrieval methods to obtain the latest information on applicants and organizations from the database. Input includes extracted applicant IDs and organization codes, which are used to query the MySQL database. Output includes detailed information such as the latest organization name, contact person name, and contact details.

[0475] Step 4:

[0476] The server updates documents using update mechanisms, based on newly acquired latest information. Input consists of past document information and the latest information retrieved from the database; an algorithm is used to apply this information to a text template. The output is an updated document, with data corrected where necessary.

[0477] Step 5:

[0478] The server compares old and new drawings using a differential reflection mechanism. The input consists of past and new drawing data, and image processing is performed using the OpenCV library. Changes in objects and their positions are identified, and differential information is generated as an output, which is then reflected in the document.

[0479] Step 6:

[0480] The server uses a generation mechanism to integrate all information and generate the final application document. The input is a dataset with differential updates and updated information completed, and the document generation engine outputs the final document in PDF or DOCX format. This document is provided to the user and stored in a downloadable format.

[0481] (Application Example 1)

[0482] 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."

[0483] Traditional application procedures in the construction sector have been time-consuming and cumbersome due to the large volume of paperwork and the complexity of update processes. Furthermore, maintaining consistency with past application documents when changes occur is difficult, and manual errors are prone to occur, thus creating a need for efficient and accurate document management. In particular, there is a growing demand for faster procedures at construction sites, and the provision of a system that can meet these needs is essential.

[0484] 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.

[0485] In this invention, the server includes means for analyzing past application documents and extracting necessary information, means for acquiring the latest data on applicant information and organizational information, and means for automatically updating the application documents based on the acquired latest information. This enables users to quickly and accurately access the latest application documents even on-site.

[0486] 1. "Application documents" refer to the documents required for an application, which are generated based on past information and new design plans.

[0487] 2. "Analysis method" refers to a technique that involves investigating past application documents and systematically extracting necessary information.

[0488] 3. "Information acquisition methods" refer to methods for gathering up-to-date data related to the applicant or organization from internal or external sources.

[0489] 4. "Update mechanism" refers to a system that automatically edits and revises existing application documents using the latest acquired information.

[0490] 5. The "difference reflection method" is a procedure that extracts the differences between past and new design drawings and applies those differences to the application document.

[0491] 6. "Generation means" refers to a system that creates the application document in its final form, revised through updates and differential updates, and provides it in digital format.

[0492] 7. A "mobile information terminal" refers to a computer terminal, such as a smartphone or tablet, that allows users to access information while on the move.

[0493] 8. "Personal information" refers to information about individual members within an organization, including details related to personnel changes in particular.

[0494] 9. "Points of concern" refers to opinions and comments that users can use to review the generated application document and request corrections or improvements as needed.

[0495] The system program that realizes this invention primarily generates application documents efficiently through processes of information extraction, data updating, and differential reflection. The server runs a Python-based program to analyze past application documents and extract necessary information. It is designed to be accessible to users via mobile information terminals such as smartphones and tablets.

[0496] The server uses information retrieval means to obtain the latest applicant and organizational information from internal or external sources. Furthermore, the server uses update means to automatically update application documents based on the retrieved data. This update includes the automatic generation of change reports based on changes in personal information.

[0497] Furthermore, the server uses a differential update mechanism to compare past and new design drawings, extract the resulting differences, and reflect them in the application document. This ensures that application documents always contain the latest information.

[0498] As a concrete example, when applying for the installation of a new base station in a construction project, the user uploads last year's documents and new drawings, and the server automatically generates an application document that reflects the latest information. This generated document is then provided to the user via their terminal.

[0499] Specific examples of prompt messages include "Generate project application documents that reflect the latest design drawings" and "Create updated documents that include changes based on past project documents." In this way, the present invention achieves faster and more accurate creation of application documents.

[0500] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0501] Step 1:

[0502] The server receives past application documents and new design drawings uploaded by the user. These files are provided to the analysis system as input data. In this step, necessary information is extracted from the past application documents using text analysis techniques. The extracted information is stored as structured data for use in subsequent processing steps.

[0503] Step 2:

[0504] The server uses information retrieval means to collect the latest information on applicants and organizations from internal or external sources. This process involves searching databases and retrieving the most recent data. This retrieved data is then entered for comparison with historical data, cross-referenced with existing information, and a dataset reflecting the current state is generated.

[0505] Step 3:

[0506] The server utilizes the update mechanism to automatically update the application document using the latest information obtained in Step 2, based on the structured data extracted in Step 1. Specifically, it verifies the consistency of the information and updates the relevant parts of the document if there are any changes. The updated document is output as the latest version containing the new information.

[0507] Step 4:

[0508] The server uses a differential update mechanism to detect differences between past design drawings and newly uploaded design drawings. This comparison process performs graphic analysis to identify changes. The detected differences are automatically reflected in the updated application document and corrected to accurately reflect the installation conditions.

[0509] Step 5:

[0510] Based on the information obtained in steps 3 and 4, the server uses a generation mechanism to create the final application document. The generated document is provided in a format accessible on the user's mobile information terminal, such as a smartphone or tablet. This allows the user to quickly review the application document and provide feedback as needed.

[0511] 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.

[0512] This invention relates to an automated application document generation system incorporating an emotion engine, with the aim of improving the efficiency of administrative application procedures and enhancing the user experience. This system includes analysis means, information acquisition means, update means, difference reflection means, generation means, and an emotion engine.

[0513] Specifically, users upload past application documents and new drawings from their terminals to the system. The server receives these files and automatically extracts the information necessary for the application using analysis tools. Next, the server uses information acquisition tools to retrieve the latest data on applicant and organizational information from internal and external databases, and automatically updates the application documents using update tools.

[0514] Furthermore, the server uses a differential update mechanism to compare the old and new drawings, extract the differences, and reflect them in the application documents. At this point, the emotion engine starts up and recognizes the user's emotions in real time during the application document generation process. If the emotion engine determines, for example, that the user is feeling stressed, it will adjust the interface to simplify operations or display guidance.

[0515] Furthermore, the server records the user's past emotional data and uses that data to personalize the experience of future application procedures. For example, it can improve the user's experience by refining procedures that were previously frustrating. Finally, the server uses a generation method to generate the final application document integrating all the information and provides the user with a download link, enabling accurate and efficient applications.

[0516] In this way, by utilizing an emotion engine, it is possible not only to streamline the application document generation process but also to improve the individual user experience. This system has the significant advantage of providing flexible support that responds to the user's emotions while maintaining the accuracy of the information.

[0517] The following describes the processing flow.

[0518] Step 1:

[0519] The user selects past application documents and new drawing files on their terminal and uploads them to the system.

[0520] Step 2:

[0521] The server receives the uploaded files and uses analysis tools to extract necessary information from the application documents, such as the applicant's name and usage period.

[0522] Step 3:

[0523] The server uses information retrieval methods to obtain applicant and organizational information from the company's latest internal database. If necessary, it also accesses external databases to obtain the latest information on the list of executives.

[0524] Step 4:

[0525] The server utilizes update mechanisms to automatically update application documents using the latest information obtained, correcting them to meet the new requirements.

[0526] Step 5:

[0527] The server uses a differential update mechanism to compare past drawings with new drawings and extract the differences. Based on these differences, it accurately updates the application documents.

[0528] Step 6:

[0529] The server activates an emotion engine to recognize the user's emotions in real time as they interact with the application documents.

[0530] Step 7:

[0531] Based on its emotion engine, the server automatically adjusts the interface and displays guidance according to the user's emotional state. For example, if the user is feeling stressed, it will offer options to simplify the operation.

[0532] Step 8:

[0533] The server generates the final version of the application documents and formats them. This process optimizes the user experience by referencing past sentiment data.

[0534] Step 9:

[0535] The server provides the user with a download link for the generated application documents. The user reviews the final documents and submits feedback as needed.

[0536] Step 10:

[0537] The server stores the received feedback along with sentiment data and uses it to improve future processes. This information is also used to personalize subsequent tasks.

[0538] (Example 2)

[0539] 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."

[0540] In administrative procedures, preparing application documents is time-consuming and laborious, and ensuring accuracy can be difficult. Furthermore, traditional application procedures often lack sufficient support to address user stress and inconvenience. Therefore, there is a need to streamline application processes and improve the user experience.

[0541] 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.

[0542] In this invention, the server includes means for analyzing past application information and extracting necessary data, means for obtaining the latest data on applicants and organizations from internal and external data management devices, and means for recognizing the user's emotions and dynamically adjusting operational support. This enables automatic updating of application information, accurate reflection of differences, and dynamic support tailored to the individual needs of the user.

[0543] "Past application information" refers to data from records and documents previously submitted by the applicant.

[0544] "Analysis" refers to the process of breaking down information, extracting the necessary elements, and organizing them.

[0545] "Latest data" refers to the most up-to-date information currently available, including any significant changes or updates to the application.

[0546] A "data management device" refers to an internal or external system for storing, managing, and retrieving information.

[0547] "Revision" refers to rewriting existing information or documents based on updated content.

[0548] "Difference" refers to a difference that becomes apparent through comparison, and in particular, it indicates inconsistencies between new and old information or data.

[0549] "User" refers to an individual or organization that operates the system and performs various procedures.

[0550] "Recognizing emotions" refers to detecting and analyzing the emotional state of a user.

[0551] "Dynamic adjustment" refers to automatically providing optimal settings and support according to the situation.

[0552] "Application information" refers to a document containing the data and related information necessary for the application procedure.

[0553] This invention is an automated application information generation system aimed at improving the efficiency of administrative application processes and enhancing the user experience. Specifically, this system has the function of analyzing past application information and extracting necessary data. Users upload past application documents and new drawing data to the system using a terminal, and subsequent processing is performed by the server.

[0554] The server first uses OCR (Optical Character Recognition) software as an analysis tool to automatically extract necessary text information from uploaded application documents. This analysis identifies important fields and aggregates them into an internal database. Subsequently, updated applicant and organization information is retrieved from internal or external data management devices using an information retrieval tool. This involves accessing external databases via a REST API to obtain the necessary and up-to-date information.

[0555] Furthermore, the server analyzes the user's emotions in real time during the application process using an emotion recognition engine. If the user is experiencing stress, the server adjusts the interface accordingly, simplifying operations or providing guidance. This emotion analysis utilizes facial recognition software and voice emotion recognition technology.

[0556] Ultimately, the server uses a generative AI model to automatically generate application information that integrates all the data. The generated application information is provided in PDF format for easy download by the user.

[0557] As a concrete example, consider a scenario where a new application for public housing is submitted, and past application documents and new housing plans are uploaded. In this case, the server automatically extracts the necessary data based on the previous application information, updates the applicant and organization information, and generates accurate and efficient new application information.

[0558] An example of a prompt message might be: "I would like to apply for a new municipal housing unit. Please extract the necessary information from my past application documents and the new housing plan, automatically update it, and generate the final application documents. If I become unsure at any point, please display a procedural guide to assist me."

[0559] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0560] Step 1:

[0561] The user selects past application documents and new drawing data from their device and uploads them to the system. The device receives the input data through a file selection dialog and sends it to the server using the HTTP protocol. The input data is stored as a user file, while the output is temporarily stored on the server.

[0562] Step 2:

[0563] The server analyzes the received files. Using OCR (Optical Character Recognition) software, it digitizes the necessary text data contained in the application documents and identifies important fields. The input data is the uploaded image file, and the output is the extracted digitized application information.

[0564] Step 3:

[0565] The server uses information acquisition methods to retrieve the latest applicant and organization information from internal and external data management devices. It accesses external databases using a REST API to retrieve data. The input in this step consists of identified key fields, and the output is the retrieved latest information.

[0566] Step 4:

[0567] The server integrates the extracted data with the latest information and performs automatic updates. Using a document generation library, it modifies the content of application documents based on the latest information and creates new application information. The input is the extracted data and the latest information, and the output is the latest application information.

[0568] Step 5:

[0569] The server uses a differential reflection mechanism to compare the old and new drawings using an image processing algorithm and extract the differences. The difference information is then reflected in the application documents. As a result, the input is the data of the old and new drawings, and the output is updated application information including the differences.

[0570] Step 6:

[0571] The server operates an emotion recognition engine to analyze the user's emotional state in real time. Using facial recognition technology and voice analysis, it adjusts the interface and guidance as needed. Input is real-time image and audio data, and output is the adjusted interface.

[0572] Step 7:

[0573] The server utilizes a generative AI model to generate the final application information, integrating all the necessary data. PDF generation software is used to create the complete application document in PDF format. The input is integrated application data, and the output is the application document in PDF format.

[0574] Step 8:

[0575] The server provides the completed application information to the user. The user can receive a download link from the server and save the file to their device. The input for this step is the generated PDF file, and the output is the application document saved on the user's device.

[0576] (Application Example 2)

[0577] 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."

[0578] In electronic transactions, users often experience emotional burdens, and there is a need to improve the user experience to ensure smooth transaction completion. However, current systems lack interface adjustments and operational support that take user emotions into consideration, hindering the smoothness of transactions. This challenge needs to be addressed.

[0579] 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.

[0580] In this invention, the server includes an analysis means for analyzing past documents and extracting necessary information, an emotion analysis means for detecting the user's emotional state and optimizing the operation procedure based on the detected emotion, and a means for evaluating the user's record state and proposing operation guides or automation of procedures as needed. This enables smoother transactions by providing an optimized interface and individual support according to the user's emotional state.

[0581] "Analysis means" refers to a device or function that analyzes past documents and automatically extracts necessary information.

[0582] "Information acquisition means" refers to a device or function that acquires the latest data on user information or organization information from an internal or external database.

[0583] "Update means" refers to a device or function that automatically updates a document based on the latest information obtained.

[0584] A "difference reflection means" is a device or function that compares past and new records, extracts the differences, and reflects those differences in a document.

[0585] "Generation means" refers to a device or function that ultimately generates a document that has been updated and differentially reflected.

[0586] "Emotional analysis means" refers to a device or function that detects the emotional state of a user and optimizes the operating procedure based on the detected emotions.

[0587] An "operation guide" is a collection of explanations and instructions provided to help users operate the system smoothly.

[0588] "Procedure automation" refers to the process of streamlining operations and procedures performed by users by having a system automatically handle them.

[0589] A description of embodiments for carrying out this invention will be given.

[0590] To realize this application, the system is configured as follows: The server receives past documents provided by the user and extracts the necessary information using analysis tools. Advanced text analysis algorithms are used for the analysis, such as services like the Google Cloud Vision API. This makes it possible to accurately extract user and organization information from documents.

[0591] The analyzed information is retrieved using an information acquisition mechanism to obtain the latest numerical data from internal or external databases. Database technologies such as SQL database management systems are used in this process to ensure accurate data acquisition. Based on the acquired data, an update mechanism automatically updates the document.

[0592] Furthermore, a differential update mechanism compares past documents with new records, extracts differences, and reflects them in the document as much as possible. At this stage, a differential analysis algorithm is used to efficiently process the differences. Finally, a generation mechanism integrates all the information, generates the updated document, and provides it to the user's terminal.

[0593] Furthermore, the system implements emotion analysis capabilities to collect facial and voice data through the user's camera and microphone, and evaluates the user's emotional state in real time. This evaluation is performed using software such as IBM Watson's emotion analysis API. Based on the evaluation results, it is possible to adjust the operation guide or suggest automating procedures to improve the user experience.

[0594] For example, if the system detects that a user is experiencing stress during a transaction, it will suggest "batch processing" or "automatic input options." This simplifies the process and provides an environment where the user can continue operating with peace of mind. Another example of an input prompt for the generated AI model might be, "The user seems anxious. How can we make the transaction process easier?"

[0595] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0596] Step 1:

[0597] Users upload past documents from their terminals to the server. The server receives these documents and extracts the necessary information using analysis tools. In this process, the input is the documents provided by the user, and the output is the extracted necessary information. The server then uses a text analysis algorithm to extract user information and organization information to obtain data.

[0598] Step 2:

[0599] The server uses information acquisition methods to collect the latest data based on information obtained from internal and external databases. The input is parsed user information, and the output is an updated set of user information. Here, SQL database queries are used to efficiently obtain the latest relevant information.

[0600] Step 3:

[0601] The server automatically updates documents based on the latest information obtained using the update mechanism. The input is the latest data, and the output is the updated document. The server uses this information to update existing documents by replacing or adding to them.

[0602] Step 4:

[0603] The server uses a differential reflection mechanism to compare past and new records, extract the differences, and reflect them in the document. The input is the past document and the latest analysis data, and the output is an updated document with the differences reflected. Based on the differential analysis algorithm, the server checks the differences and adds or modifies the document.

[0604] Step 5:

[0605] The server generates the final document based on the information integrated by the generation mechanism. The input is the document reflecting the differences, and the output is the final generated document. The server completes the document by integrating all the information while verifying its consistency.

[0606] Step 6:

[0607] The server uses emotion analysis tools to detect the user's emotional state from the user's camera and microphone data. The input is the user's real-time video and audio data, and the output is the emotional state. Here, the IBM Watson emotion analysis API is used to evaluate the user's emotions.

[0608] Step 7:

[0609] The server suggests operation guides and automated procedures based on the user's emotional state. The input is the detected emotional state, and the output is the adjusted or suggested interface or procedure. It provides the user with operation options and suggests efficient procedures through prompts.

[0610] 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.

[0611] 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 those described above. 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 shown 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.

[0612] 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.

[0613] [Fourth Embodiment]

[0614] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0615] 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.

[0616] 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).

[0617] 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.

[0618] 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.

[0619] 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).

[0620] 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.

[0621] 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.

[0622] 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.

[0623] 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.

[0624] 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.

[0625] 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.

[0626] 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".

[0627] This invention relates to a system for automating and streamlining the application process when installing base stations on properties owned by administrative agencies. This system includes analysis means, information acquisition means, update means, difference reflection means, and generation means.

[0628] Specifically, users upload past application documents and new drawings to the system. Upon receiving this information, the server first uses an analysis tool to extract necessary information from the past application documents. Then, the server uses an information retrieval tool to obtain the latest data on applicant and organizational information from the database.

[0629] Next, the server utilizes update mechanisms to automatically update application documents based on the latest acquired data, reflecting the new information. If there are changes due to personnel changes within the organization, the server automatically generates the appropriate change notification and reflects it as the latest information.

[0630] Furthermore, the server uses a differential reflection mechanism to compare past drawings with new drawings and identify the differences. These differences are automatically reflected in the application documents, ensuring that accurate documents are prepared according to the new installation conditions.

[0631] Finally, the server generates the final application document based on all the information. This generated document is provided to the user and can be downloaded or printed as needed.

[0632] For example, in the case of an application for the installation of a new base station, the user uploads the documents from the previous year, reflects changes in organizational information due to recent organizational reforms, and checks the differences with the newly provided drawings. This allows for the preparation of accurate application documents in a short time, resulting in labor savings and a reduction in errors.

[0633] The following describes the processing flow.

[0634] Step 1:

[0635] The user selects past application documents and new drawing files from their terminal and uploads them to the system.

[0636] Step 2:

[0637] The server receives the uploaded files and uses analysis tools to extract necessary information from past application documents, such as the applicant's name, start date of use, and loan period.

[0638] Step 3:

[0639] The server uses information retrieval methods to access internal databases and obtain the latest information on applicants, the organization's current board of directors, and other relevant data. External databases are also referenced as needed.

[0640] Step 4:

[0641] The server uses an update mechanism to automatically update the contents of past application documents based on the latest information it has obtained, and creates documents that meet the current application requirements.

[0642] Step 5:

[0643] When the server receives information from a user regarding changes such as personnel transfers within the organization, it automatically generates an appropriate change notification form based on that information and adds it to the documents.

[0644] Step 6:

[0645] The server uses a differential update mechanism to compare past drawings with new drawings and extract the changes. The extracted differences are then appropriately reflected in the application documents.

[0646] Step 7:

[0647] The server generates the final application documents, formats them, and then provides the user with a downloadable link. The user reviews the completed documents and submits feedback as needed.

[0648] (Example 1)

[0649] 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".

[0650] Manually updating information in past application documents and ensuring consistency with new drawings during the application process is extremely time-consuming and carries a high risk of human error. In this context, there is a growing need for a system that enables efficient and accurate information updates and differential reflection.

[0651] 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.

[0652] In this invention, the server includes an analysis means, an information acquisition means, an update means, a difference reflection means, and a generation means. This enables the automatic extraction of past document information, acquisition of the latest information, updating of documents, reflection of differences by comparing old and new drawings, and generation of the final document.

[0653] "Analysis means" refers to the techniques and processes for extracting necessary information from historical documents.

[0654] "Information acquisition means" refers to the technology and processes for obtaining the latest information on applicants or organizations from data storage devices or external information sources.

[0655] "Update means" refers to the technology and process that automatically corrects and updates document content based on the latest acquired information.

[0656] "Difference reflection means" refers to the technology and process of comparing past drawings with new drawings, detecting the differences, and reflecting them in the document.

[0657] "Generation method" refers to the technology and process used to create the final document after updates and differential changes have been applied.

[0658] This invention relates to a system for automating and streamlining the application process for providing basic data documents for properties owned by government agencies. The system begins with the user uploading past application documents and new design drawings to the system.

[0659] Specifically, users upload past application documents and new drawing data to a cloud-based system using their devices. The server receives the uploaded data and first extracts necessary information from the past documents using analysis tools. This process utilizes optical character recognition (OCR) technology and natural language processing tools for text analysis. As a result, the contents of the documents are organized as digital information.

[0660] Next, the server uses information retrieval methods to obtain the latest information on applicants and organizations from data storage devices, specifically database management systems such as MySQL and PostgreSQL. The data is retrieved efficiently using SQL queries.

[0661] Based on the latest information obtained, the server utilizes update mechanisms to automatically update documents. A dedicated algorithm is applied to reflect changes in organizational information and assigned personnel in the documents.

[0662] Furthermore, the server uses a difference-reflection mechanism to compare old and new drawings. Utilizing the OpenCV library, it detects differences in the drawings using image processing technology and reflects them in the document. This ensures the creation of accurate documents that reflect changes in installation conditions.

[0663] Ultimately, the generation process produces a document containing all the information. This document, created in PDF or DOCX format, is provided to the user, who can download or print it according to their needs.

[0664] As a concrete example, when applying for the installation of a new base station, the user uploads the application documents from the previous year, and a document reflecting the information updates due to recent organizational reforms and differences in new drawings is quickly generated. This is expected to simplify the procedure and allow it to proceed more efficiently.

[0665] An example of a prompt for the generated AI model would be: "Please describe the automated system that reflects the latest organizational information and drawing changes required for administrative procedures."

[0666] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0667] Step 1:

[0668] The user uploads past application documents and new drawing data to the cloud-based system using a terminal. Input includes past application documents (PDF format) and new design drawings (CAD file format). This data is sent to the system and prepared for processing on the server.

[0669] Step 2:

[0670] When the server receives uploaded past application documents, it uses analysis tools to extract the necessary information. The input is a PDF document, which is converted into text data using optical character recognition (OCR) technology. From the extracted text data, necessary information such as the applicant's name, application details, and date is identified using natural language processing (NLP) and output as structured data.

[0671] Step 3:

[0672] The server uses information retrieval methods to obtain the latest information on applicants and organizations from the database. Input includes extracted applicant IDs and organization codes, which are used to query the MySQL database. Output includes detailed information such as the latest organization name, contact person name, and contact details.

[0673] Step 4:

[0674] The server updates documents using update mechanisms, based on newly acquired latest information. Input consists of past document information and the latest information retrieved from the database; an algorithm is used to apply this information to a text template. The output is an updated document, with data corrected where necessary.

[0675] Step 5:

[0676] The server compares old and new drawings using a differential reflection mechanism. The input consists of past and new drawing data, and image processing is performed using the OpenCV library. Changes in objects and their positions are identified, and differential information is generated as an output, which is then reflected in the document.

[0677] Step 6:

[0678] The server uses a generation mechanism to integrate all information and generate the final application document. The input is a dataset with differential updates and updated information completed, and the document generation engine outputs the final document in PDF or DOCX format. This document is provided to the user and stored in a downloadable format.

[0679] (Application Example 1)

[0680] 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".

[0681] Traditional application procedures in the construction sector have been time-consuming and cumbersome due to the large volume of paperwork and the complexity of update processes. Furthermore, maintaining consistency with past application documents when changes occur is difficult, and manual errors are prone to occur, thus creating a need for efficient and accurate document management. In particular, there is a growing demand for faster procedures at construction sites, and the provision of a system that can meet these needs is essential.

[0682] 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.

[0683] In this invention, the server includes means for analyzing past application documents and extracting necessary information, means for acquiring the latest data on applicant information and organizational information, and means for automatically updating the application documents based on the acquired latest information. This enables users to quickly and accurately access the latest application documents even on-site.

[0684] 1. "Application documents" refer to the documents required for an application, which are generated based on past information and new design plans.

[0685] 2. "Analysis method" refers to a technique that involves investigating past application documents and systematically extracting necessary information.

[0686] 3. "Information acquisition methods" refer to methods for gathering up-to-date data related to the applicant or organization from internal or external sources.

[0687] 4. "Update mechanism" refers to a system that automatically edits and revises existing application documents using the latest acquired information.

[0688] 5. The "difference reflection method" is a procedure that extracts the differences between past and new design drawings and applies those differences to the application document.

[0689] 6. "Generation means" refers to a system that creates the application document in its final form, revised through updates and differential updates, and provides it in digital format.

[0690] 7. A "mobile information terminal" refers to a computer terminal, such as a smartphone or tablet, that allows users to access information while on the move.

[0691] 8. "Personal information" refers to information about individual members within an organization, including details related to personnel changes in particular.

[0692] 9. "Points of concern" refers to opinions and comments that users can use to review the generated application document and request corrections or improvements as needed.

[0693] The system program that realizes this invention primarily generates application documents efficiently through processes of information extraction, data updating, and differential reflection. The server runs a Python-based program to analyze past application documents and extract necessary information. It is designed to be accessible to users via mobile information terminals such as smartphones and tablets.

[0694] The server uses information retrieval means to obtain the latest applicant and organizational information from internal or external sources. Furthermore, the server uses update means to automatically update application documents based on the retrieved data. This update includes the automatic generation of change reports based on changes in personal information.

[0695] Furthermore, the server uses a differential update mechanism to compare past and new design drawings, extract the resulting differences, and reflect them in the application document. This ensures that application documents always contain the latest information.

[0696] As a concrete example, when applying for the installation of a new base station in a construction project, the user uploads last year's documents and new drawings, and the server automatically generates an application document that reflects the latest information. This generated document is then provided to the user via their terminal.

[0697] Specific examples of prompt messages include "Generate project application documents that reflect the latest design drawings" and "Create updated documents that include changes based on past project documents." In this way, the present invention achieves faster and more accurate creation of application documents.

[0698] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0699] Step 1:

[0700] The server receives past application documents and new design drawings uploaded by the user. These files are provided to the analysis system as input data. In this step, necessary information is extracted from the past application documents using text analysis techniques. The extracted information is stored as structured data for use in subsequent processing steps.

[0701] Step 2:

[0702] The server uses information retrieval means to collect the latest information on applicants and organizations from internal or external sources. This process involves searching databases and retrieving the most recent data. This retrieved data is then entered for comparison with historical data, cross-referenced with existing information, and a dataset reflecting the current state is generated.

[0703] Step 3:

[0704] The server utilizes the update mechanism to automatically update the application document using the latest information obtained in Step 2, based on the structured data extracted in Step 1. Specifically, it verifies the consistency of the information and updates the relevant parts of the document if there are any changes. The updated document is output as the latest version containing the new information.

[0705] Step 4:

[0706] The server uses a differential update mechanism to detect differences between past design drawings and newly uploaded design drawings. This comparison process performs graphic analysis to identify changes. The detected differences are automatically reflected in the updated application document and corrected to accurately reflect the installation conditions.

[0707] Step 5:

[0708] Based on the information obtained in steps 3 and 4, the server uses a generation mechanism to create the final application document. The generated document is provided in a format accessible on the user's mobile information terminal, such as a smartphone or tablet. This allows the user to quickly review the application document and provide feedback as needed.

[0709] 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.

[0710] This invention relates to an automated application document generation system incorporating an emotion engine, with the aim of improving the efficiency of administrative application procedures and enhancing the user experience. This system includes analysis means, information acquisition means, update means, difference reflection means, generation means, and an emotion engine.

[0711] Specifically, users upload past application documents and new drawings from their terminals to the system. The server receives these files and automatically extracts the information necessary for the application using analysis tools. Next, the server uses information acquisition tools to retrieve the latest data on applicant and organizational information from internal and external databases, and automatically updates the application documents using update tools.

[0712] Furthermore, the server uses a differential update mechanism to compare the old and new drawings, extract the differences, and reflect them in the application documents. At this point, the emotion engine starts up and recognizes the user's emotions in real time during the application document generation process. If the emotion engine determines, for example, that the user is feeling stressed, it will adjust the interface to simplify operations or display guidance.

[0713] Furthermore, the server records the user's past emotional data and uses that data to personalize the experience of future application procedures. For example, it can improve the user's experience by refining procedures that were previously frustrating. Finally, the server uses a generation method to generate the final application document integrating all the information and provides the user with a download link, enabling accurate and efficient applications.

[0714] In this way, by utilizing an emotion engine, it is possible not only to streamline the application document generation process but also to improve the individual user experience. This system has the significant advantage of providing flexible support that responds to the user's emotions while maintaining the accuracy of the information.

[0715] The following describes the processing flow.

[0716] Step 1:

[0717] The user selects past application documents and new drawing files on their terminal and uploads them to the system.

[0718] Step 2:

[0719] The server receives the uploaded files and uses analysis tools to extract necessary information from the application documents, such as the applicant's name and usage period.

[0720] Step 3:

[0721] The server uses information retrieval methods to obtain applicant and organizational information from the company's latest internal database. If necessary, it also accesses external databases to obtain the latest information on the list of executives.

[0722] Step 4:

[0723] The server utilizes update mechanisms to automatically update application documents using the latest information obtained, correcting them to meet the new requirements.

[0724] Step 5:

[0725] The server uses a differential update mechanism to compare past drawings with new drawings and extract the differences. Based on these differences, it accurately updates the application documents.

[0726] Step 6:

[0727] The server activates an emotion engine to recognize the user's emotions in real time as they interact with the application documents.

[0728] Step 7:

[0729] Based on its emotion engine, the server automatically adjusts the interface and displays guidance according to the user's emotional state. For example, if the user is feeling stressed, it will offer options to simplify the operation.

[0730] Step 8:

[0731] The server generates the final version of the application documents and formats them. This process optimizes the user experience by referencing past sentiment data.

[0732] Step 9:

[0733] The server provides the user with a download link for the generated application documents. The user reviews the final documents and submits feedback as needed.

[0734] Step 10:

[0735] The server stores the received feedback along with sentiment data and uses it to improve future processes. This information is also used to personalize subsequent tasks.

[0736] (Example 2)

[0737] 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".

[0738] In administrative procedures, preparing application documents is time-consuming and laborious, and ensuring accuracy can be difficult. Furthermore, traditional application procedures often lack sufficient support to address user stress and inconvenience. Therefore, there is a need to streamline application processes and improve the user experience.

[0739] 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.

[0740] In this invention, the server includes means for analyzing past application information and extracting necessary data, means for obtaining the latest data on applicants and organizations from internal and external data management devices, and means for recognizing the user's emotions and dynamically adjusting operational support. This enables automatic updating of application information, accurate reflection of differences, and dynamic support tailored to the individual needs of the user.

[0741] "Past application information" refers to data from records and documents previously submitted by the applicant.

[0742] "Analysis" refers to the process of breaking down information, extracting the necessary elements, and organizing them.

[0743] "Latest data" refers to the most up-to-date information currently available, including any significant changes or updates to the application.

[0744] A "data management device" refers to an internal or external system for storing, managing, and retrieving information.

[0745] "Revision" refers to rewriting existing information or documents based on updated content.

[0746] "Difference" refers to a difference that becomes apparent through comparison, and in particular, it indicates inconsistencies between new and old information or data.

[0747] "User" refers to an individual or organization that operates the system and performs various procedures.

[0748] "Recognizing emotions" refers to detecting and analyzing the emotional state of a user.

[0749] "Dynamic adjustment" refers to automatically providing optimal settings and support according to the situation.

[0750] "Application information" refers to a document containing the data and related information necessary for the application procedure.

[0751] This invention is an automated application information generation system aimed at improving the efficiency of administrative application processes and enhancing the user experience. Specifically, this system has the function of analyzing past application information and extracting necessary data. Users upload past application documents and new drawing data to the system using a terminal, and subsequent processing is performed by the server.

[0752] The server first uses OCR (Optical Character Recognition) software as an analysis tool to automatically extract necessary text information from uploaded application documents. This analysis identifies important fields and aggregates them into an internal database. Subsequently, updated applicant and organization information is retrieved from internal or external data management devices using an information retrieval tool. This involves accessing external databases via a REST API to obtain the necessary and up-to-date information.

[0753] Furthermore, the server analyzes the user's emotions in real time during the application process using an emotion recognition engine. If the user is experiencing stress, the server adjusts the interface accordingly, simplifying operations or providing guidance. This emotion analysis utilizes facial recognition software and voice emotion recognition technology.

[0754] Ultimately, the server uses a generative AI model to automatically generate application information that integrates all the data. The generated application information is provided in PDF format for easy download by the user.

[0755] As a concrete example, consider a scenario where a new application for public housing is submitted, and past application documents and new housing plans are uploaded. In this case, the server automatically extracts the necessary data based on the previous application information, updates the applicant and organization information, and generates accurate and efficient new application information.

[0756] An example of a prompt message might be: "I would like to apply for a new municipal housing unit. Please extract the necessary information from my past application documents and the new housing plan, automatically update it, and generate the final application documents. If I become unsure at any point, please display a procedural guide to assist me."

[0757] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0758] Step 1:

[0759] The user selects past application documents and new drawing data from their device and uploads them to the system. The device receives the input data through a file selection dialog and sends it to the server using the HTTP protocol. The input data is stored as a user file, while the output is temporarily stored on the server.

[0760] Step 2:

[0761] The server analyzes the received files. Using OCR (Optical Character Recognition) software, it digitizes the necessary text data contained in the application documents and identifies important fields. The input data is the uploaded image file, and the output is the extracted digitized application information.

[0762] Step 3:

[0763] The server uses information acquisition methods to retrieve the latest applicant and organization information from internal and external data management devices. It accesses external databases using a REST API to retrieve data. The input in this step consists of identified key fields, and the output is the retrieved latest information.

[0764] Step 4:

[0765] The server integrates the extracted data with the latest information and performs automatic updates. Using a document generation library, it modifies the content of application documents based on the latest information and creates new application information. The input is the extracted data and the latest information, and the output is the latest application information.

[0766] Step 5:

[0767] The server uses a differential reflection mechanism to compare the old and new drawings using an image processing algorithm and extract the differences. The difference information is then reflected in the application documents. As a result, the input is the data of the old and new drawings, and the output is updated application information including the differences.

[0768] Step 6:

[0769] The server operates an emotion recognition engine to analyze the user's emotional state in real time. Using facial recognition technology and voice analysis, it adjusts the interface and guidance as needed. Input is real-time image and audio data, and output is the adjusted interface.

[0770] Step 7:

[0771] The server utilizes a generative AI model to generate the final application information, integrating all the necessary data. PDF generation software is used to create the complete application document in PDF format. The input is integrated application data, and the output is the application document in PDF format.

[0772] Step 8:

[0773] The server provides the completed application information to the user. The user can receive a download link from the server and save the file to their device. The input for this step is the generated PDF file, and the output is the application document saved on the user's device.

[0774] (Application Example 2)

[0775] 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".

[0776] In electronic transactions, users often experience emotional burdens, and there is a need to improve the user experience to ensure smooth transaction completion. However, current systems lack interface adjustments and operational support that take user emotions into consideration, hindering the smoothness of transactions. This challenge needs to be addressed.

[0777] 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.

[0778] In this invention, the server includes an analysis means for analyzing past documents and extracting necessary information, an emotion analysis means for detecting the user's emotional state and optimizing the operation procedure based on the detected emotion, and a means for evaluating the user's record state and proposing operation guides or automation of procedures as needed. This enables smoother transactions by providing an optimized interface and individual support according to the user's emotional state.

[0779] "Analysis means" refers to a device or function that analyzes past documents and automatically extracts necessary information.

[0780] "Information acquisition means" refers to a device or function that acquires the latest data on user information or organization information from an internal or external database.

[0781] "Update means" refers to a device or function that automatically updates a document based on the latest information obtained.

[0782] A "difference reflection means" is a device or function that compares past and new records, extracts the differences, and reflects those differences in a document.

[0783] "Generation means" refers to a device or function that ultimately generates a document that has been updated and differentially reflected.

[0784] "Emotional analysis means" refers to a device or function that detects the emotional state of a user and optimizes the operating procedure based on the detected emotions.

[0785] An "operation guide" is a collection of explanations and instructions provided to help users operate the system smoothly.

[0786] "Procedure automation" refers to the process of streamlining operations and procedures performed by users by having a system automatically handle them.

[0787] A description of embodiments for carrying out this invention will be given.

[0788] To realize this application, the system is configured as follows: The server receives past documents provided by the user and extracts the necessary information using analysis tools. Advanced text analysis algorithms are used for the analysis, such as services like the Google Cloud Vision API. This makes it possible to accurately extract user and organization information from documents.

[0789] The analyzed information is retrieved using an information acquisition mechanism to obtain the latest numerical data from internal or external databases. Database technologies such as SQL database management systems are used in this process to ensure accurate data acquisition. Based on the acquired data, an update mechanism automatically updates the document.

[0790] Furthermore, a differential update mechanism compares past documents with new records, extracts differences, and reflects them in the document as much as possible. At this stage, a differential analysis algorithm is used to efficiently process the differences. Finally, a generation mechanism integrates all the information, generates the updated document, and provides it to the user's terminal.

[0791] Furthermore, the system implements emotion analysis capabilities to collect facial and voice data through the user's camera and microphone, and evaluates the user's emotional state in real time. This evaluation is performed using software such as IBM Watson's emotion analysis API. Based on the evaluation results, it is possible to adjust the operation guide or suggest automating procedures to improve the user experience.

[0792] For example, if the system detects that a user is experiencing stress during a transaction, it will suggest "batch processing" or "automatic input options." This simplifies the process and provides an environment where the user can continue operating with peace of mind. Another example of an input prompt for the generated AI model might be, "The user seems anxious. How can we make the transaction process easier?"

[0793] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0794] Step 1:

[0795] Users upload past documents from their terminals to the server. The server receives these documents and extracts the necessary information using analysis tools. In this process, the input is the documents provided by the user, and the output is the extracted necessary information. The server then uses a text analysis algorithm to extract user information and organization information to obtain data.

[0796] Step 2:

[0797] The server uses information acquisition methods to collect the latest data based on information obtained from internal and external databases. The input is parsed user information, and the output is an updated set of user information. Here, SQL database queries are used to efficiently obtain the latest relevant information.

[0798] Step 3:

[0799] The server automatically updates documents based on the latest information obtained using the update mechanism. The input is the latest data, and the output is the updated document. The server uses this information to update existing documents by replacing or adding to them.

[0800] Step 4:

[0801] The server uses a differential reflection mechanism to compare past and new records, extract the differences, and reflect them in the document. The input is the past document and the latest analysis data, and the output is an updated document with the differences reflected. Based on the differential analysis algorithm, the server checks the differences and adds or modifies the document.

[0802] Step 5:

[0803] The server generates the final document based on the information integrated by the generation mechanism. The input is the document reflecting the differences, and the output is the final generated document. The server completes the document by integrating all the information while verifying its consistency.

[0804] Step 6:

[0805] The server uses emotion analysis tools to detect the user's emotional state from the user's camera and microphone data. The input is the user's real-time video and audio data, and the output is the emotional state. Here, the IBM Watson emotion analysis API is used to evaluate the user's emotions.

[0806] Step 7:

[0807] The server suggests operation guides and automated procedures based on the user's emotional state. The input is the detected emotional state, and the output is the adjusted or suggested interface or procedure. It provides the user with operation options and suggests efficient procedures through prompts.

[0808] 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.

[0809] 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 those described above. 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 shown 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.

[0810] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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."

[0817] 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.

[0818] 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.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] The following is further disclosed regarding the embodiments described above.

[0830] (Claim 1)

[0831] An analysis means characterized by analyzing past application documents and extracting necessary information,

[0832] Information acquisition means for obtaining the latest data on applicant information and organizational information from internal or external databases,

[0833] A means of updating application documents automatically based on the latest information obtained,

[0834] A difference-reflection method that compares past and new drawings, extracts the differences, and reflects those differences in the application documents,

[0835] A generation method for ultimately generating application documents that have been updated and differentially reflected,

[0836] A system that includes this.

[0837] (Claim 2)

[0838] The system according to claim 1, comprising a procedure for automatically generating a change notification based on updates to personnel information within the applicant's organization.

[0839] (Claim 3)

[0840] The system according to claim 1, comprising a procedure for providing generated application documents to a user and receiving feedback from the user.

[0841] "Example 1"

[0842] (Claim 1)

[0843] An analysis means characterized by analyzing past documents and extracting necessary information,

[0844] Information acquisition means for obtaining the latest data of applicant information and organizational information from a data storage device,

[0845] A means of updating documents automatically based on the latest information obtained,

[0846] A difference reflection method that compares past and new drawings, extracts the differences, and reflects those differences in the document,

[0847] A generation means for ultimately generating a document that has been updated and differentially reflected,

[0848] A system that includes this.

[0849] (Claim 2)

[0850] The system according to claim 1, comprising a procedure for automatically generating change notifications based on updates to personnel information within the organization.

[0851] (Claim 3)

[0852] The system according to claim 1, comprising a procedure for providing generated documents to users and receiving feedback from users.

[0853] "Application Example 1"

[0854] (Claim 1)

[0855] A method for analyzing past application documents and extracting necessary information,

[0856] Means for obtaining the latest data on applicant information and organizational information from internal or external sources,

[0857] A means to automatically update application documents based on the latest information obtained,

[0858] A means of comparing past and new design drawings, extracting the differences, and reflecting those differences in the application documents,

[0859] A means to finally generate an updated application document with reflected differences and make it accessible via a mobile information terminal,

[0860] A system that includes this.

[0861] (Claim 2)

[0862] The system according to claim 1, comprising a procedure for automatically generating a change report based on updates to personal information within the applicant's organization.

[0863] (Claim 3)

[0864] The system according to claim 1, comprising a procedure for providing the generated application document to the user and receiving comments from the user via a mobile information terminal.

[0865] "Example 2 of combining an emotion engine"

[0866] (Claim 1)

[0867] A method for analyzing past application information and extracting necessary data,

[0868] A means of obtaining the latest data on applicant information and organization information from internal and external data management devices,

[0869] A means to automatically correct application information based on the latest acquired data,

[0870] A method for comparing past and new drawings, extracting differences, and reflecting those differences in the application information,

[0871] A means of recognizing the user's emotions during the application process and dynamically adjusting the operational support,

[0872] A means to create the final application information after making corrections and reflecting the differences,

[0873] A system that includes this.

[0874] (Claim 2)

[0875] The system according to claim 1, comprising a procedure for automatically generating a change notification based on modifications to the placement information within the applicant's organization.

[0876] (Claim 3)

[0877] The system according to claim 1, comprising a procedure for providing generated application information to a user and obtaining feedback from the user.

[0878] "Application example 2 when combining with an emotional engine"

[0879] (Claim 1)

[0880] An analysis means characterized by analyzing past documents and extracting necessary information,

[0881] Information acquisition means for obtaining the latest data on user information and organization information from internal or external databases,

[0882] A means of updating documents automatically based on the latest information obtained,

[0883] A difference reflection method that compares past and new records, extracts the differences, and reflects those differences in the document,

[0884] A generation means for ultimately generating a document that has been updated and differentially reflected,

[0885] An emotion analysis means that detects the user's emotional state and optimizes the operating procedure based on the detected emotion,

[0886] A system that includes this.

[0887] (Claim 2)

[0888] The system according to claim 1, comprising a procedure for evaluating the user's record status and, if necessary, proposing operation guides or automation of procedures.

[0889] (Claim 3)

[0890] The system according to claim 1, comprising a procedure for providing the generated document to the user, receiving the user's emotional feedback, and using it to improve future user experiences. [Explanation of symbols]

[0891] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A method for analyzing past application documents and extracting necessary information, Means for obtaining the latest data on applicant information and organizational information from internal or external sources, A means to automatically update application documents based on the latest information obtained, A means of comparing past and new design drawings, extracting the differences, and reflecting those differences in the application documents, A means to finally generate an updated application document with reflected differences and make it accessible via a mobile information terminal, A system that includes this.

2. The system according to claim 1, comprising a procedure for automatically generating a change report based on updates to personal information within the applicant's organization.

3. The system according to claim 1, comprising a procedure for providing the generated application document to the user and receiving comments from the user via a mobile information terminal.

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