system

Abstract

We provide the system. [Solution] A means of uploading the business manual file, A means to analyze the contents of uploaded business manuals and extract business processes and elements, A means of generating a requirements definition diagram based on the extracted information, A method for selecting the parts to be systematized from the requirements definition diagram, A means of analyzing the detailed requirements of the selected portion and displaying them using a visualization tool, A method for comparing the operational manual with the systemized process and calculating the time reduction effect, Means for providing systemization solutions and specific programming methods, A system that includes this.

Description

Technical Field

[0004] , ,

[0005] , , ,

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] A "business manual" is a document that describes in detail the procedures and processes implemented by a company or organization.

[0007] "Uploading" refers to the act of a user transferring files from their device to a server.

[0008] "Analysis" is the process by which a system examines the input data in detail and extracts useful information from it.

[0009] A "business process" refers to a series of steps and activities required to perform a specific task.

[0010] An "element" is a fundamental, individual part that makes up a system or process.

[0011] A "requirements definition diagram" is a diagram that visually represents the requirements and specifications of the business processes to be systematized.

[0012] "Selection" means choosing a specific item from among several options.

[0013] "Detailed requirements" refer to the specific elements and conditions necessary for system implementation.

[0014] A "visualization tool" is software or a system for visually displaying data and information.

[0015] The "time reduction effect" refers to the reduction of business hours achieved by systemization.

[0016] A "systemization solution" refers to a method or means for incorporating a specific business process into a system for automation.

[0017] A "programming method" refers to a method of designing and writing software code for realizing specific operations and functions.

Brief Explanation of Drawings

[0018] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0019] 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.

[0020] First, the terms used in the following description will be described.

[0021] 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.

[0022] 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.

[0023] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0024] 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).

[0025] 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."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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".

[0039] This invention relates to a system that automates and streamlines the process from analyzing business manuals to systematizing them. The program processing of this system is described below in natural language.

[0040] Uploading and analyzing business manuals

[0041] The user uploads a business manual file from their terminal to the server. The server receives this file and begins analysis. Specifically, the server converts the file's contents into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This allows for the extraction of business processes and elements.

[0042] Generation of Requirements Definition Diagrams

[0043] The server automatically generates a requirements definition diagram based on the extracted business processes and elements. The requirements definition diagram visually represents the flow of business processes and is provided in a format that is easy for the user to understand. The server uses a flowchart generation library to create a visual requirements definition diagram and displays it to the user through a web interface.

[0044] Selection and analysis of the systematization components

[0045] Users can select the parts they want to automate from the generated requirements definition diagram. The selected data is sent from the terminal to the server, which then performs a detailed analysis of those parts. The analysis results are displayed to the user using a detailed visualization tool. This allows the user to understand the details of the specific business processes to be automated.

[0046] Calculation of time-saving effect

[0047] The server compares the contents of the operational manual with the systematized process and calculates the time savings. This calculation uses a statistical algorithm to specifically show how much work time is saved through systemization. The calculation results are visualized and presented to the user.

[0048] Providing system solutions and programming methods.

[0049] Based on the analysis results and user requirements, the server proposes the optimal systemization solution. This may include specific software frameworks and API combinations. Furthermore, the server automatically generates specific programming methods and provides them to the user. The provided programming methods include sample code and programming procedures, allowing the user to proceed with implementation based on these.

[0050] Specific example: Systematization of product inventory management

[0051] For example, if a user uploads a business manual for "product inventory management," the system will operate as follows:

[0052] 1. The user uploads the product inventory management manual file from their terminal to the server.

[0053] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[0054] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[0055] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[0056] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[0057] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[0058] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[0059] This allows users to smoothly define requirements based on business manuals and achieve efficient system implementation.

[0060] The following describes the processing flow.

[0061] Step 1:

[0062] The user uploads the work manual file from their terminal to the server. The user uses the terminal's web interface to select the work manual file and clicks the upload button. The terminal then sends the selected file to the server.

[0063] Step 2:

[0064] The server receives the uploaded business manual and begins analysis. The server converts the file contents into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This allows for the extraction of business processes and elements.

[0065] Step 3:

[0066] The server generates a requirements definition diagram based on the extracted information. The server analyzes the business process flow and uses a flowchart generation library to create a visual requirements definition diagram. The server displays the generated requirements definition diagram to the user through a web interface.

[0067] Step 4:

[0068] The user selects the parts they want to automate from the requirements diagram. The user reviews the displayed requirements diagram and clicks to select the parts they want to automate. The terminal sends the selected data to the server.

[0069] Step 5:

[0070] The server performs a detailed analysis of the selected portion. Based on the received data, the server performs a detailed analysis of the selected business process and generates detailed visualizations (flowcharts and ER diagrams). The server displays the generated diagrams to the user via a web interface.

[0071] Step 6:

[0072] The server compares the contents of the operational manual with the process after systemization and calculates the time savings. The server uses statistical algorithms to calculate the time saved by systemization. The calculation results are visualized and presented to the user.

[0073] Step 7:

[0074] The server provides the optimal systemization solution and specific programming methods. Based on the analysis results and user requirements, the server selects the appropriate systemization solution and automatically generates sample code and programming procedures. The server then presents this to the user through a web interface.

[0075] The above describes the detailed flow of program processing in the "RequirementsCraft" system and the specific actions performed at each processing step.

[0076] (Example 1)

[0077] 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."

[0078] The requirements definition and system development associated with the systemization of traditional business processes were often manual, time-consuming, and labor-intensive. Furthermore, there were concerns about errors and decreased efficiency in the process of extracting systemization requirements from business manuals. Additionally, the effectiveness of systemization was difficult to evaluate concretely beforehand, making the post-implementation effects uncertain. This led to delays in systemization aimed at improving business efficiency.

[0079] 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.

[0080] In this invention, the server includes means for uploading business procedure manual files, means for analyzing the contents of the uploaded business procedure manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting the parts to be systematized from the requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a visualization tool, means for comparing the business procedure manuals with the systematized processes and calculating the time reduction effect, and means for providing systematization solutions and specific programming methods. This makes it possible to automatically extract systematization requirements from business manuals and efficiently build systems. Furthermore, by evaluating the effects of systematization in advance, concrete effects can be expected before implementation.

[0081] A "work procedure manual" is a document that describes work processes and procedures, clearly outlining how to perform the work, the roles involved, and the conditions.

[0082] "Uploading" refers to the action of sending a file from a device to a server, and means transmitting digital data over the internet.

[0083] "Analysis" refers to the process of analyzing the content of data or documents to extract specific information or patterns.

[0084] A "business process" refers to a series of business procedures or activities performed to achieve a specific objective.

[0085] An "element" is a specific item or part that makes up a business process, and includes procedures, roles, triggers, conditions, etc.

[0086] A "requirements definition diagram" is a diagram that visually represents the interrelationships between business processes and elements, showing the flow and relationships of business procedures.

[0087] "Systematization" refers to the introduction of computer systems to automate business processes that are currently performed manually.

[0088] "Selection" refers to the act of choosing a specific item from among multiple options.

[0089] "Detailed requirements" refers to the specific conditions and specifications necessary for system implementation.

[0090] A "visualization tool" is a software tool used to visually display data and information, and includes tools that generate graphs, charts, and flowcharts.

[0091] "Time-saving effect" refers to the effect of streamlining business processes through systemization, thereby reducing the time required.

[0092] A "statistical algorithm" refers to a mathematical method used to analyze data and derive statistical conclusions or predictions.

[0093] A "systemization solution" refers to the optimal methods and technical proposals for systematizing specific business processes.

[0094] "Programming methods" refer to the specific coding procedures and techniques used to build computer systems.

[0095] This invention is a system that automatically automates the analysis of work procedure manuals to improve efficiency. Specifically, it consists of the following means.

[0096] First, the user uploads the work procedure manual file from their terminal to the server. This upload is done via an HTML form or a file upload API. The user selects the work procedure manual file (e.g., PDF, Word, etc.) and submits it by clicking the "Upload" button.

[0097] Next, the server analyzes the contents of the uploaded business procedure manual. This analysis uses Apache® Tika to convert the file into text data and then uses Python's natural language processing module (e.g., NLTK, spaCy) to identify elements such as business procedures, roles, triggers, and conditions. In this process, business processes and elements are identified and extracted.

[0098] Next, the server generates a requirements definition diagram based on the extracted information. A flowchart generation library (e.g., Graphviz, PlantUML) is used to create a visual requirements definition diagram. This requirements definition diagram is in a user-friendly format, and the server displays this diagram to the user through a web interface.

[0099] From the displayed requirements diagram, the user selects the parts they want to automate. This selection is made by clicking on the requirements diagram, and the selection data is sent from the terminal to the server. The server performs a detailed analysis of the selected parts and uses a natural language processing module again to identify specific procedures and necessary resources. The analysis results are generated as detailed flowcharts and data flow diagrams and provided to the user.

[0100] Furthermore, the server compares the manual work procedures with the systemized processes and calculates the time savings using statistical algorithms. This calculation uses tools such as Python's pandas and scikit-learn, and the results are visualized and presented to the user as graphs and charts. For example, it might show a specific effect such as, "Systematizing the inventory update process can reduce time by 50%."

[0101] Finally, the server proposes the optimal systemization solution based on the analysis results and user requirements. This may include specific software frameworks (e.g., Django, Flask) and API combinations. The server also automatically generates specific programming methods and provides the user with sample code and programming instructions, allowing the user to proceed with implementation.

[0102] Specific example: Systematization of product inventory management

[0103] For example, if a user uploads a business procedure manual for "product inventory management," the system will operate as follows:

[0104] 1. The user uploads a product inventory management procedure file from their terminal to the server.

[0105] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[0106] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[0107] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[0108] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[0109] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[0110] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[0111] Examples of prompts to input into a generative AI model

[0112] When inputting a specific example of what happens when a user uploads a "Product Inventory Management Procedure Manual" into the AI ​​model, use the following prompt message:

[0113] The user uploaded a business procedure manual for product inventory management from their terminal to the server. The server analyzed the manual, extracted business processes such as "order taking," "procurement," and "inventory updating," and displayed an automatically generated requirements definition diagram to the user. The user chose to automate the "inventory updating process," and the server generated a detailed flowchart and provided it to the user. It was calculated that this would reduce the time required by 50% compared to the traditional manual process, and this result was presented to the user. Finally, the server proposed a solution using the "inventory module of the ERP system" and provided the user with program examples, including specific API call codes.

[0114] According to the embodiment for carrying out this invention, the process from uploading work procedure manuals to systemization and calculation of time-saving effects is efficiently executed.

[0115] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0116] Step 1: Upload the operational procedures manual.

[0117] The user uploads the work procedure manual file from their terminal to the server. The user selects the file using the browser's file upload function and clicks the "Upload" button. The input file can be in formats such as PDF or Word, and the output is a file saved on the server. This process imports the work procedure manual to the server.

[0118] Step 2: Analysis of operational procedures

[0119] The server analyzes the uploaded business procedure manuals. First, the server uses the Apache Tika library to convert the files into text data. The converted text is then analyzed using a natural language processing module (e.g., NLTK or spaCy) to identify elements such as business procedures, roles, triggers, and conditions. The input is text data, and the output is the result of extracting business processes and elements. Specifically, business processes such as "order taking," "inventory check," and "shipping preparation" are identified.

[0120] Step 3: Generating the Requirements Definition Diagram

[0121] The server generates a requirements definition diagram based on the extracted business processes and elements. The server creates a visual flowchart using a flowchart generation library (e.g., Graphviz or PlantUML). This flowchart shows the flow of the business process and is displayed in an easy-to-understand format for the user. The input is the extracted business process results, and the output is the generated requirements definition diagram. The requirements definition diagram is displayed to the user via a browser.

[0122] Step 4: Selecting the parts to be systematized

[0123] The user selects the parts they want to automate from the generated requirements diagram. The user makes this selection by clicking on the business processes they want to automate within the requirements diagram. The input is the requirements diagram, and the output is the data for the selected parts to be automated. This data is sent from the terminal to the server.

[0124] Step 5: Detailed analysis of the systemized portion

[0125] The server performs a detailed analysis of the systemization portion selected by the user. Using a natural language processing module again, it identifies the corresponding specific steps and required resources for the selected portion. The input is the data of the selected systemization portion, and the output is a detailed flowchart or data flow diagram. The analysis results are displayed to the user using a visualization tool (e.g., D3.js).

[0126] Step 6: Calculating the time-saving effect

[0127] The server compares the contents of the work procedure manual with the systematized process and calculates the time reduction effect using a statistical algorithm. The server analyzes the data using Python's pandas and scikit-learn to calculate how much work time is reduced by the systematization. The input is the analysis results of the work procedure manual and the process data after systematization, and the output is a report on the time reduction effect. The calculation results are presented to the user as a graph.

[0128] Step 7: Provide systemization solutions and programming methods.

[0129] The server proposes the optimal systemization solution based on the analysis results and user requirements. The server suggests specific software frameworks (e.g., Django, Flask) and API combinations, and automatically generates concrete programming instructions. The input is the analysis results and user selections, and the output is the proposed systemization solution and program examples. The generated program examples and procedures are provided to the user via a web interface.

[0130] (Application Example 1)

[0131] 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."

[0132] Traditional process for systematizing operational manuals required significant time and effort, from manual analysis and requirements definition to system selection and provision of programming methods. Furthermore, in environments demanding high efficiency, such as logistics centers, efficient work instructions and real-time procedure verification based on operational manuals were difficult, often leading to delays and errors. In particular, product inspection and inventory management required employees to memorize numerous procedures, which reduced work efficiency. There is a need to solve these problems and improve operational efficiency and accuracy.

[0133] 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.

[0134] In this invention, the server includes means for uploading business manual files, means for analyzing the contents of the uploaded business manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting parts to be systematized from the requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a visualization tool, means for comparing the business manual with the systematized process and calculating the time reduction effect, means for providing a systematization solution and a specific program, and means for displaying business procedures on smart glasses and instructing the next step via voice control. This automates and streamlines the systematization process of business manuals, enabling real-time display of appropriate procedures and voice-controlled next instructions, particularly in product inspection and inventory work at logistics centers.

[0135] "A means of uploading business manual files" refers to a mechanism for users to transfer document files containing procedures and rules related to their work to a server.

[0136] "A means of analyzing the contents of uploaded business manuals and extracting business processes and elements" refers to a system in which the server reads the contents of the received business manuals as digital data and uses natural language processing technology to identify elements such as business procedures and roles.

[0137] "A means of generating requirements definition diagrams based on extracted information" refers to a mechanism for creating visual flowcharts based on analyzed business flows and elements.

[0138] "A means of selecting the parts to be systematized from the requirements definition diagram" refers to a mechanism that allows users to review the generated requirements definition diagram and select the specific business processes they want to systematize.

[0139] "A means of analyzing the detailed requirements of the selected portion and displaying them with a visualization tool" refers to a system that further analyzes the business portion selected by the user and graphically displays the analysis results to the user.

[0140] "A method for comparing business manuals with systemized processes and calculating time savings" refers to a mechanism that compares traditional business procedures with systemized procedures and uses statistical algorithms to calculate how much time is saved after systemization.

[0141] "Means of providing systemized solutions and specific programs" refers to a mechanism that provides users with solutions utilizing specific software frameworks and APIs, as well as specific methods for their implementation, in order to improve the efficiency of business operations.

[0142] "A means of displaying work procedures on smart glasses and instructing the next step via voice control" refers to a system that uses the display of smart glasses to show work procedures and utilizes voice recognition functionality to instruct the next step in response to the worker's commands.

[0143] This invention is a system for improving the efficiency of product inspection and inventory management in logistics centers. The system's program processing and the hardware and software used are described in detail below.

[0144] The server first accepts user uploads of business manual files. To analyze the contents of the business manual, OCR (Optical Character Recognition) technology is used to convert it into text data, and then a natural language processing module (e.g., SpaCy, NLTK) is used. This allows elements such as business procedures, roles, triggers, and conditions to be extracted.

[0145] Based on the extracted information, the server generates a requirements definition diagram. This diagram is created using a flowchart generation library (e.g., Graphviz) and visually represents the business process. The generated requirements definition diagram is displayed on the user's terminal via a web interface.

[0146] Next, the user reviews the requirements definition diagram and selects the specific parts they want to automate. A detailed analysis of the selected parts is then performed, and the results are visualized in detail using a visualization tool (e.g., D3.js). This allows the user to understand the details of the business processes of the selected parts.

[0147] The server also compares the operational manual with the systemized process and calculates the time-saving effect. Using statistical algorithms, it calculates how much work time will be reduced by systemization and presents the results to the user.

[0148] Furthermore, the server provides optimal systemization solutions and specific programming methods based on the analysis results and user requirements. This includes the use of specific software frameworks and APIs.

[0149] Employees at the logistics center wear smart glasses (e.g., Google® Glass®, Vuzix) and perform their tasks while checking the work procedures displayed on the glasses. The smart glasses accept the next instruction using voice recognition, which allows them to display appropriate work instructions in real time.

[0150] Specific example

[0151] For example, when employees perform product inspection work at a logistics center, they wear smart glasses. The glasses display instructions such as "Please scan the product," and when they say "next" via voice prompt, the next step, "Please check the condition of the product," is displayed. This allows employees to work efficiently while confirming the steps.

[0152] Example of a prompt

[0153] "Upload the operational manual and use OCR and natural language processing to extract the operational procedures. Display the extracted procedures on smart glasses and use voice recognition to detect the next instruction and proceed to the next step."

[0154] In this way, this invention automates everything from the analysis of operational manuals to the systemization process, resulting in a significant improvement in operational efficiency at logistics centers.

[0155] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0156] Step 1:

[0157] The user uploads a work manual file from their terminal to the server. When the user selects the work manual file from their terminal and presses the "Upload" button, the file is transferred to the server. In this process, the input is the work manual file, and the output is the file being saved on the server.

[0158] Step 2:

[0159] The server analyzes the content of the uploaded business manuals and extracts business processes and elements. First, the server uses OCR technology to convert the business manuals into text data. Next, it uses a natural language processing module (e.g., SpaCy, NLTK) to identify business procedures, roles, triggers, and conditions. In this process, the input is text data, and the output is the extracted business processes and elements. Specifically, the OCR module analyzes image data, and the natural language processing module analyzes text to identify specific elements.

[0160] Step 3:

[0161] Based on the extracted information, the server generates a requirements definition diagram. This is done using a flowchart generation library (e.g., Graphviz). The input is the extracted business processes and elements, and the output is a visual requirements definition diagram. The server converts the flow of business processes into a diagram using the library and presents it in a user-friendly format.

[0162] Step 4:

[0163] The user selects the parts they want to automate from the requirements diagram. The server displays the requirements diagram via a web interface, allowing the user to select the parts they want to automate using mouse clicks or taps. The input is the entire requirements diagram, and the output is the data for the parts selected by the user. The server accepts user input and understands the selected parts.

[0164] Step 5:

[0165] The server analyzes the detailed requirements of the selected portion and displays them using a visualization tool (e.g., D3.js). It analyzes the selected data in detail and displays the results graphically. The input is the data of the selected business portion, and the output is a visualization of the detailed analysis results. Specifically, it analyzes the selected data in detail and depicts the analysis results as a diagram.

[0166] Step 6:

[0167] The server compares the contents of the operational manual with the systemized process and calculates the time reduction effect. A statistical algorithm is used for this calculation. Inputs include analysis results and data on the systemized process, while output is a specific numerical value regarding the time reduction effect. The comparison algorithm is used to process the data and calculate the time reduction effect.

[0168] Step 7:

[0169] The server provides systemization solutions and specific programming methods. This includes the use of specific software frameworks and APIs. Inputs are analysis results and user requirements, while outputs are recommended solutions and specific programming methods. Based on the analysis data, the server selects the optimal solution and generates specific program examples.

[0170] Step 8:

[0171] The smart glasses display work procedures and provide voice commands to guide the user to the next step. The smart glasses' display shows the work procedures, and voice recognition (e.g., Google Speech-to-Text) is used to accept the next instruction. Input consists of work procedures and voice commands, while output is a display of the next step. Specifically, the smart glasses display the next step based on the voice command they detect.

[0172] 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.

[0173] This invention relates to a system that automates and streamlines the process from analyzing business manuals to systematizing them. This system incorporates an emotion engine that recognizes user emotions and has the function to adjust the interface and provide support according to the user's emotional state. The program processing of this system is described below in natural language.

[0174] Uploading and analyzing business manuals

[0175] The user uploads the work manual file from their terminal to the server. The user uses the terminal's web interface to select the work manual file and clicks the upload button. The terminal then sends the selected file to the server.

[0176] The server receives the uploaded business manual content and begins analysis. The server converts the file content into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This allows for the extraction of business processes and elements.

[0177] Generation of Requirements Definition Diagrams

[0178] The server automatically generates a requirements definition diagram based on the extracted business processes and elements. The requirements definition diagram visually represents the flow of business processes and is provided in a format that is easy for the user to understand. The server uses a flowchart generation library to create a visual requirements definition diagram and displays it to the user through a web interface.

[0179] Selection and analysis of the systematization components

[0180] Users can select the parts they want to automate from the generated requirements definition diagram. The selected data is sent from the terminal to the server, which then performs a detailed analysis of those parts. The analysis results are displayed to the user using a detailed visualization tool. This allows the user to understand the details of the specific business processes to be automated.

[0181] Calculation of time-saving effect

[0182] The server compares the contents of the operational manual with the systematized process and calculates the time savings. This calculation uses a statistical algorithm to specifically show how much work time is saved through systemization. The calculation results are visualized and presented to the user.

[0183] Providing system solutions and programming methods.

[0184] Based on the analysis results and user requirements, the server proposes the optimal systemization solution. This may include specific software frameworks and API combinations. Furthermore, the server automatically generates specific programming methods and provides them to the user. The provided programming methods include sample code and programming procedures, allowing the user to proceed with implementation based on these.

[0185] Utilizing the Emotion Engine

[0186] During user interaction, the emotion engine recognizes the user's emotional state. This emotion engine analyzes the user's emotions through voice and text analysis. Based on the analysis results, the server adjusts the interface according to the user's emotional state. For example, if the user is feeling confused or frustrated, the system will adjust to provide more detailed explanations and guidance. Support messages and guidance will also be provided according to the user's emotional state.

[0187] Specific example: Systematization of product inventory management

[0188] For example, if a user uploads a business manual for "product inventory management," the system will operate as follows:

[0189] 1. The user uploads the product inventory management manual file from their terminal to the server.

[0190] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[0191] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[0192] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[0193] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[0194] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[0195] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[0196] 8. The emotion engine analyzes the user's emotions from their voice and text, and if the user is confused, the system adjusts the interface to provide more detailed explanations or additional guidance.

[0197] This allows users to smoothly define requirements based on operational manuals and achieve efficient system implementation. The use of an emotion engine improves the user experience, leading to further efficiency improvements and increased user satisfaction.

[0198] The following describes the processing flow.

[0199] Step 1:

[0200] The user uploads the work manual file from their terminal to the server. The user selects the work manual file through the terminal's web interface and clicks the upload button. The terminal then sends the selected file to the server.

[0201] Step 2:

[0202] The server receives the uploaded business manual and begins analysis. The server converts the file contents into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This extracts the business processes and elements.

[0203] Step 3:

[0204] The server generates a requirements definition diagram based on the extracted information. The server uses a flowchart generation library to automatically generate flowcharts of business processes. The generated requirements definition diagram is displayed to the user through a web interface in a visually easy-to-understand format.

[0205] Step 4:

[0206] The user selects the parts they want to automate from the generated requirements diagram. The user reviews the requirements diagram and clicks to select the parts they wish to automate. The terminal sends the data for the selected parts to the server.

[0207] Step 5:

[0208] The server performs a detailed analysis of the selected portion. Based on the received data, the server performs a detailed analysis of the selected business process. The server uses detailed visualization tools to generate the analysis results as visual flowcharts and ER diagrams, which are then displayed to the user.

[0209] Step 6:

[0210] The server compares the contents of the operational manual with the process after systemization and calculates the time savings. The server uses a statistical algorithm to calculate the time saved by systemization. The calculation results are visualized and presented to the user.

[0211] Step 7:

[0212] The server provides the optimal systemization solution and specific programming methods. Based on the analysis results and user requirements, the server selects the optimal systemization solution (such as a combination of specific software frameworks and APIs). Furthermore, the server automatically generates sample code and programming instructions and provides them to the user.

[0213] Step 8:

[0214] The emotion engine recognizes the user's emotional state. The terminal and server collect the user's emotions through voice or text input, and the emotion engine analyzes this data. Based on the analysis results, the server adjusts the interface according to the user's emotional state. For example, if the user is confused, the server provides detailed explanations or additional guidance.

[0215] Specific example: Systematization of product inventory management

[0216] Step 1:

[0217] The user uploads the "Product Inventory Management" business manual file to the server using a terminal.

[0218] Step 2:

[0219] The server receives the uploaded manual, converts it into text data, applies a natural language processing module, and extracts business processes such as "order placement," "procurement," and "inventory update."

[0220] Step 3:

[0221] The server generates a requirements definition diagram based on the extracted information and displays this diagram, including the "flow from order placement to inventory update," to the user.

[0222] Step 4:

[0223] The user reviews the requirements diagram and selects to automate the "inventory update process." The terminal then sends the selected data to the server.

[0224] Step 5:

[0225] The server analyzes the details of the "inventory update process," generates a detailed flowchart, and displays it to the user.

[0226] Step 6:

[0227] The server calculates the time saved by systematizing the inventory update process and presents to the user that a 50% time reduction is possible compared to the traditional manual process.

[0228] Step 7:

[0229] The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, including specific API call code.

[0230] Step 8:

[0231] The emotion engine analyzes the user's emotions from their voice and text, and if the user appears confused, the server adjusts the interface to provide more detailed explanations and additional guidance.

[0232] (Example 2)

[0233] 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".

[0234] Automating the entire process, from analyzing existing business manuals and generating requirements definition diagrams to implementing systems and improving operational efficiency, is challenging. Furthermore, to enhance the user experience, it's necessary to accurately recognize the user's emotional state during operation and for the system to respond appropriately accordingly. A system is needed that can efficiently and appropriately address these challenges.

[0235] 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.

[0236] In this invention, the server includes means for uploading electronic files of business manuals, means for analyzing the contents of the uploaded business manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting parts to be systematized from the generated requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a detailed visualization tool, means for comparing the business manual with the systematized process and calculating the time reduction effect using statistical methods, means for providing a systematization solution and specific programming methods, and means including an emotion engine that adjusts the interface based on the user's emotional state. As a result, the process from business manual analysis to systematization is automated, enabling improved user experience and a significant increase in business efficiency.

[0237] A "business manual" is a document that outlines work procedures, roles, rules, and other information within a company or organization.

[0238] An "electronic file" is a digital document or data file that can be handled by a computer.

[0239] "Uploading" refers to the act of transferring data or files from a user's device to a server or cloud storage.

[0240] A "natural language processing module" is software or an algorithm that analyzes natural language data, such as text and speech, to extract and understand its meaning.

[0241] A "business process" is a set of steps and activities necessary to complete a specific task.

[0242] A "requirements definition diagram" is a diagram that visually represents business processes and elements, and serves as the foundation for system development.

[0243] A "visualization tool" is software used to visually display and analyze data and information.

[0244] A "statistical algorithm" refers to statistical methods and calculation procedures used for data analysis and prediction.

[0245] A "systemization solution" refers to specific technical measures or proposals aimed at automating and streamlining business processes.

[0246] "Programming method" refers to the way a program is written or the procedures involved in achieving a specific task or solution.

[0247] An "emotion engine" is software or a system that analyzes a user's emotional state in real time and provides appropriate feedback and interface adjustments.

[0248] This invention relates to a system that automates and streamlines the process from analyzing business manuals to systematizing them. This system incorporates an emotion engine that recognizes the user's emotional state and has functions to adjust the interface and provide support.

[0249] Uploading and analyzing business manuals

[0250] The user uploads an electronic file of the work manual from their terminal to the server. The user uses the terminal's web interface to select the work manual file and clicks the upload button. The terminal sends the selected file to the server via an HTTP POST request. The server parses the received file and converts it into text data. This parsing is performed using a natural language processing module (e.g., spaCy or NLTK) to identify elements such as work procedures, roles, triggers, and conditions.

[0251] Generation of Requirements Definition Diagrams

[0252] The server generates a requirements definition diagram using a flowchart drawing library (e.g., Graphviz) based on the extracted business processes and elements. The requirements definition diagram is displayed to the user via a web interface, allowing the user to visually understand the business processes.

[0253] Selection and analysis of the systematization components

[0254] The user selects the part of the requirements diagram they want to automate via a web interface. For example, the user selects the "Inventory Update" process by clicking on it. The selected data is sent from the terminal to the server, which then performs a detailed analysis of that part. The analysis results are displayed to the user using a detailed visualization tool (e.g., D3.js).

[0255] Calculation of time-saving effect

[0256] The server compares the contents of the operational manual with the systematized process and calculates the time savings. This calculation uses a statistical algorithm (e.g., Scikit-learn in Python) to specifically demonstrate the time savings achieved through systematization. The calculation results are visualized and presented to the user.

[0257] Providing system solutions and programming methods.

[0258] Based on the analysis results and user requirements, the server proposes an appropriate systemization solution. For example, it might suggest "using the inventory module of an ERP system." This proposal would also include appropriate frameworks and APIs (e.g., Django or Flask). The server provides specific programming methods and offers sample code and programming instructions to help the user implement the solution.

[0259] Utilizing the Emotion Engine

[0260] While the user is interacting with the system, the emotion engine recognizes the user's emotional state. This emotion engine analyzes the user's emotions through speech analysis (e.g., Google Speech-to-Text API) and text analysis (e.g., OpenAI® GPT). Based on the analysis results, the server adjusts the interface according to the user's emotional state. For example, if the user is feeling confused or frustrated, the system will adjust to provide detailed explanations and guidance.

[0261] Specific example: Systematization of product inventory management

[0262] For example, if a user uploads a business manual for "product inventory management," the system will operate as follows:

[0263] 1. The user uploads the product inventory management manual file from their terminal to the server.

[0264] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[0265] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[0266] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[0267] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[0268] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[0269] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[0270] 8. The emotion engine analyzes the user's emotions from their voice and text, and if the user is confused, the system adjusts the interface to provide more detailed explanations or additional guidance.

[0271] Example of a prompt

[0272] "Please upload the product inventory management operations manual, generate a requirements definition diagram, and systematize the inventory update process."

[0273] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0274] Step 1: Select and upload the business manual file.

[0275] The user uploads an electronic file of the work manual from their terminal to the server. The user uses the terminal's web interface to click the "Select File" button and chooses the work manual file. This action sends the selected file to the server when the user clicks the upload button. The server receives the HTTP POST request and stores the work manual file. Here, the input is the electronic file of the work manual selected by the user, and the output is the file stored on the server.

[0276] Step 2: Analyze the contents of the operational manual

[0277] The server analyzes the received business manual file. First, the server converts the file into text data, and then uses a natural language processing module (e.g., spaCy or NLTK) to identify elements such as business procedures, roles, triggers, and conditions. The input here is the text data of the business manual stored on the server, and the output is the extracted elements such as business procedures and roles. Specifically, the process involves analyzing the text content, extracting keywords and phrases, and converting it into structured data.

[0278] Step 3: Generating the Requirements Definition Diagram

[0279] The server generates a requirements definition diagram using a flowchart drawing library (e.g., Graphviz) based on the extracted business processes and elements. The generated requirements definition diagram is displayed to the user via a web interface. The input here is the extracted business processes and elements, and the output is the requirements definition diagram. Specifically, the operation involves converting the extracted data into a visual flowchart and displaying it in a user-friendly format.

[0280] Step 4: Selecting the parts to be systematized

[0281] The user selects the part on the requirements definition diagram that they want to systematize on the web interface. For example, by clicking on the "Inventory Update" process, that part is selected. The selected data is sent from the terminal to the server. The input here is a part of the requirements definition diagram selected by the user, and the output is the selected data sent to the server. Specific operations include clicking on a specific part of the interface and selecting the part to be systematized.

[0282] Step 5: Detailed Analysis and Visualization

[0283] The server performs a detailed analysis of the selected part and displays it to the user using a detailed visualization tool (e.g., D3.js). The input here is a part of the requirements definition diagram selected by the user, and the output is the detailed analysis result and its visualization data. Specific operations include data analysis of the selected part, generation of a detailed flowchart, and display on the interface.

[0284] Step 6: Calculation of Time Reduction Effect

[0285] The server compares the content of the business manual with the systematized process and calculates the time reduction effect. Statistical algorithms (e.g., Scikit-learn in Python) are used for this calculation. The input here is the analysis result of the business manual and the data of the systematized process, and the output is the calculation result of the time reduction effect. Specific operations include time comparison between manual operations and the systematized process, effect calculation using statistical methods, and visualization of the results.

[0286] Step 7: Provision of Systematization Solution and Programming Method

[0287] The server proposes the optimal systemization solution based on the analysis results and user requirements. For example, it might suggest "using the inventory module of the ERP system." It also provides specific programming methods (code examples and programming procedures). The input here is the analysis results and user requirements, while the output is the proposed solution and programming method. Specific operations include evaluating the analysis results, selecting an appropriate solution, and providing specific programming procedures.

[0288] Step 8: Utilizing the Emotional Engine

[0289] While the user is interacting with the system, the emotion engine recognizes the user's emotional state and adjusts the interface accordingly. This emotion engine uses speech analysis (e.g., Google Speech-to-Text API) and text analysis (e.g., OpenAI's GPT). The input is the user's voice or text data, and the output is the emotion analysis results and the adjusted interface. Specific operations include real-time analysis of the user's voice and text, identification of emotional state, and dynamic adjustment of the interface.

[0290] (Application Example 2)

[0291] 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 device 14 will be referred to as the "terminal."

[0292] Traditional systemization processes based on operational manuals require manual analysis and requirements definition, which are extremely time-consuming and labor-intensive. This results in decreased productivity and makes it difficult to improve operational efficiency. Furthermore, the inability to adjust the interface and provide support based on user emotions makes it difficult to improve the user experience.

[0293] 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.

[0294] In this invention, the server includes means for uploading business manual files, means for analyzing the contents of the uploaded business manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting parts to be systematized from the requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a visualization tool, means for comparing the business manual with the systematized process and calculating the time reduction effect, means for providing a systematization solution and specific programming methods, and means for adjusting the interface and support according to the user's emotional state using an emotion engine that recognizes the user's emotions. As a result, the analysis and systematization of business manuals are automated, significantly reducing labor and time, while enabling flexible support that responds to the user's emotions.

[0295] A "business manual" is a document that contains detailed explanations of specific business procedures, roles, triggers, and conditions.

[0296] "Method of uploading" refers to the function or interface that allows users to send work manual files from their terminal to the server.

[0297] The "means of analysis" refer to a function that converts the content of uploaded business manuals into text data and extracts business processes and elements using natural language processing technology.

[0298] A "requirements definition diagram" is a diagram that visually represents the flow and process of business operations, making it easy for users to understand.

[0299] "Systematizing" refers to automating business processes that were previously performed manually and improving efficiency through the use of software and systems.

[0300] A "visualization tool" is a tool or interface used to visually display analyzed data or process flows.

[0301] The "time reduction effect" refers to the amount of time reduced compared to the conventional manual operations when the operations are systematized.

[0302] The "systematization solution" refers to a combination of software frameworks and APIs optimized for automating specific business processes.

[0303] The "programming method" is a method of implementing a program including specific procedures and sample codes for systematization.

[0304] The "emotion engine" is a technology for recognizing the emotional state of a user through voice analysis and text analysis, and adjusting the interface and support based on the results.

[0305] The "interface" refers to the screen display and operation means for a user to interact with the system.

[0306] The "support" refers to the guidance and auxiliary information provided when a user uses the system.

[0307] This invention aims to efficiently perform systematization based on the operation manual of robots used in a factory. In particular, a system that can visually provide information to a user using smart glasses and provide support according to the user's state by an emotion engine will be described.

[0308] Uploading and Analyzing the Business Manual

[0309] First, the user uploads the robot operation manual from their device to the server via smart glasses. Using the smart glasses' user interface, they select the manual file and send it to the cloud server. The server receives the uploaded manual and converts it into text data. The software used here includes a natural language processing (NLP) module, which extracts work procedures, roles, and other relevant information.

[0310] Generation of Requirements Definition Diagrams

[0311] The server automatically generates a requirements definition diagram based on the extracted business processes and elements. This process uses a flowchart generation library to visually represent the business flow. The generated requirements definition diagram is displayed on the smart glasses screen.

[0312] Selection and analysis of the systematization components

[0313] Users select the parts they want to systemize from a requirements definition diagram using smart glasses. The selected data is sent from the terminal to the server, which then performs a detailed analysis of that part. During this process, a detailed process flow is displayed using a visualization tool.

[0314] Calculation of time-saving effect

[0315] The server compares the contents of the operational manual with the systematized process and calculates the time-saving effect using a statistical algorithm. The calculation results are visualized and presented to the user.

[0316] Providing system solutions and programming methods.

[0317] Furthermore, the server proposes the optimal systemization solution based on the analysis results and user selections. This includes specific software frameworks, API usage methods, and sample code. This enables efficient implementation.

[0318] Utilizing the Emotion Engine

[0319] When a user uses smart glasses, the emotion engine recognizes the user's emotional state through voice and text analysis. For example, if the user is confused, the system provides a detailed explanation. The interface is also adjusted and support messages are provided according to the emotional state.

[0320] Specific example

[0321] For example, a new factory operator uploads a robot initial setup manual to smart glasses. The system extracts the robot operation procedures and generates an initial setup flowchart. The operator follows the flowchart displayed on the smart glasses, performing the operations step by step. If there are any questions, the glasses' emotion engine detects the operator's confusion and automatically displays detailed explanations or video tutorials. This allows even inexperienced operators to set up the robot with confidence.

[0322] Example of a prompt

[0323] Please describe the entire process of a system that automatically generates requirements definition diagrams from factory robot operation manuals and displays them to users using smart glasses, and provide a concrete example of how to use an emotion engine for user support.

[0324] This invention automates the analysis and systematization of business manuals, resulting in a significant reduction in labor and time, while also enabling flexible support tailored to the user's needs.

[0325] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0326] Step 1:

[0327] Uploading the business manual

[0328] The user selects a robot operation manual file using the user interface of the smart glasses and presses the upload button. This sends the selected manual file from the terminal (smart glasses) to the server.

[0329] Input: Business manual file

[0330] Output: Business manual file uploaded to the server

[0331] Step 2:

[0332] Analysis of business manuals

[0333] The server receives the uploaded business manual file and converts its contents into text data. A natural language processing (NLP) module is used to extract business processes and elements (procedures, roles, triggers, conditions, etc.).

[0334] Input: Uploaded business manual file

[0335] Output: Extracted business processes and elements

[0336] Step 3:

[0337] Generation of Requirements Definition Diagrams

[0338] The server uses a flowchart generation library to automatically generate requirements definition diagrams based on the extracted business processes and elements. The generated requirements definition diagrams are saved in the cloud and displayed on smart glasses.

[0339] Input: Extracted business processes and elements

[0340] Output: Requirements definition diagram

[0341] Step 4:

[0342] Selection of Systematization Components

[0343] The user selects the parts of the requirements diagram they want to automate through the display interface of their smart glasses. The selected data is then sent from the device to the server.

[0344] Input: Requirements definition diagram

[0345] Output: Selected systemization portion

[0346] Step 5:

[0347] Detailed analysis and visualization

[0348] The server analyzes the selected system components in detail and generates a detailed process flow. The generated flow is then displayed to the user in an easy-to-understand format using a visualization tool.

[0349] Input: Selected systemization portion

[0350] Output: Detailed process flow

[0351] Step 6:

[0352] Calculation of time-saving effect

[0353] The server compares the contents of the operational manual with the systematized process and uses a statistical algorithm to calculate the time savings. The calculation results are visualized and displayed on smart glasses.

[0354] Input: Detailed process flow

[0355] Output: Calculation results of time reduction effect

[0356] Step 7:

[0357] Providing system solutions and programming methods.

[0358] The server proposes the optimal systemization solution based on the analysis results and user requests. Furthermore, it provides specific program sample code and instructions on how to use the API.

[0359] Input: Calculation result of time reduction effect

[0360] Output: Systematized solution and specific program steps

[0361] Step 8:

[0362] Utilizing the Emotion Engine

[0363] When a user uses smart glasses, the emotion engine recognizes the user's emotional state through voice analysis and eye tracking. For example, if the user is confused, the system displays a detailed explanation or video tutorial.

[0364] Input: User sentiment data

[0365] Output: Interface adjustments and support information tailored to user sentiment.

[0366] 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.

[0367] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search)<url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0368] 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.

[0369] [Second Embodiment]

[0370] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0371] 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.

[0372] 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).

[0373] 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.

[0374] 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.

[0375] 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).

[0376] 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.

[0377] 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.

[0378] 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.

[0379] 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.

[0380] 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.

[0381] 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".

[0382] This invention relates to a system that automates and streamlines the process from analyzing business manuals to systematizing them. The program processing of this system is described below in natural language.

[0383] Uploading and analyzing business manuals

[0384] The user uploads a business manual file from their terminal to the server. The server receives this file and begins analysis. Specifically, the server converts the file's contents into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This allows for the extraction of business processes and elements.

[0385] Generation of Requirements Definition Diagrams

[0386] The server automatically generates a requirements definition diagram based on the extracted business processes and elements. The requirements definition diagram visually represents the flow of business processes and is provided in a format that is easy for the user to understand. The server uses a flowchart generation library to create a visual requirements definition diagram and displays it to the user through a web interface.

[0387] Selection and analysis of the systematization components

[0388] Users can select the parts they want to automate from the generated requirements definition diagram. The selected data is sent from the terminal to the server, which then performs a detailed analysis of those parts. The analysis results are displayed to the user using a detailed visualization tool. This allows the user to understand the details of the specific business processes to be automated.

[0389] Calculation of time-saving effect

[0390] The server compares the contents of the operational manual with the systematized process and calculates the time savings. This calculation uses a statistical algorithm to specifically show how much work time is saved through systemization. The calculation results are visualized and presented to the user.

[0391] Providing system solutions and programming methods.

[0392] Based on the analysis results and user requirements, the server proposes the optimal systemization solution. This may include specific software frameworks and API combinations. Furthermore, the server automatically generates specific programming methods and provides them to the user. The provided programming methods include sample code and programming procedures, allowing the user to proceed with implementation based on these.

[0393] Specific example: Systematization of product inventory management

[0394] For example, if a user uploads a business manual for "product inventory management," the system will operate as follows:

[0395] 1. The user uploads the product inventory management manual file from their terminal to the server.

[0396] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[0397] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[0398] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[0399] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[0400] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[0401] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[0402] This allows users to smoothly define requirements based on business manuals and achieve efficient system implementation.

[0403] The following describes the processing flow.

[0404] Step 1:

[0405] The user uploads the work manual file from their terminal to the server. The user uses the terminal's web interface to select the work manual file and clicks the upload button. The terminal then sends the selected file to the server.

[0406] Step 2:

[0407] The server receives the uploaded business manual and begins analysis. The server converts the file contents into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This allows for the extraction of business processes and elements.

[0408] Step 3:

[0409] The server generates a requirements definition diagram based on the extracted information. The server analyzes the business process flow and uses a flowchart generation library to create a visual requirements definition diagram. The server displays the generated requirements definition diagram to the user through a web interface.

[0410] Step 4:

[0411] The user selects the parts they want to automate from the requirements diagram. The user reviews the displayed requirements diagram and clicks to select the parts they want to automate. The terminal sends the selected data to the server.

[0412] Step 5:

[0413] The server performs a detailed analysis of the selected portion. Based on the received data, the server performs a detailed analysis of the selected business process and generates detailed visualizations (flowcharts and ER diagrams). The server displays the generated diagrams to the user via a web interface.

[0414] Step 6:

[0415] The server compares the contents of the operational manual with the process after systemization and calculates the time savings. The server uses statistical algorithms to calculate the time saved by systemization. The calculation results are visualized and presented to the user.

[0416] Step 7:

[0417] The server provides the optimal systemization solution and specific programming methods. Based on the analysis results and user requirements, the server selects the appropriate systemization solution and automatically generates sample code and programming procedures. The server then presents this to the user through a web interface.

[0418] The above describes the detailed flow of program processing in the "RequirementsCraft" system and the specific actions performed at each processing step.

[0419] (Example 1)

[0420] 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".

[0421] The requirements definition and system development associated with the systemization of traditional business processes were often manual, time-consuming, and labor-intensive. Furthermore, there were concerns about errors and decreased efficiency in the process of extracting systemization requirements from business manuals. Additionally, the effectiveness of systemization was difficult to evaluate concretely beforehand, making the post-implementation effects uncertain. This led to delays in systemization aimed at improving business efficiency.

[0422] 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.

[0423] In this invention, the server includes means for uploading business procedure manual files, means for analyzing the contents of the uploaded business procedure manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting the parts to be systematized from the requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a visualization tool, means for comparing the business procedure manuals with the systematized processes and calculating the time reduction effect, and means for providing systematization solutions and specific programming methods. This makes it possible to automatically extract systematization requirements from business manuals and efficiently build systems. Furthermore, by evaluating the effects of systematization in advance, concrete effects can be expected before implementation.

[0424] A "work procedure manual" is a document that describes work processes and procedures, clearly outlining how to perform the work, the roles involved, and the conditions.

[0425] "Uploading" refers to the action of sending a file from a device to a server, and means transmitting digital data over the internet.

[0426] "Analysis" refers to the process of analyzing the content of data or documents to extract specific information or patterns.

[0427] A "business process" refers to a series of business procedures or activities performed to achieve a specific objective.

[0428] An "element" is a specific item or part that makes up a business process, and includes procedures, roles, triggers, conditions, etc.

[0429] A "requirements definition diagram" is a diagram that visually represents the interrelationships between business processes and elements, showing the flow and relationships of business procedures.

[0430] "Systematization" refers to the introduction of computer systems to automate business processes that are currently performed manually.

[0431] "Selection" refers to the act of choosing a specific item from among multiple options.

[0432] "Detailed requirements" refers to the specific conditions and specifications necessary for system implementation.

[0433] A "visualization tool" is a software tool used to visually display data and information, and includes tools that generate graphs, charts, and flowcharts.

[0434] "Time-saving effect" refers to the effect of streamlining business processes through systemization, thereby reducing the time required.

[0435] A "statistical algorithm" refers to a mathematical method used to analyze data and derive statistical conclusions or predictions.

[0436] A "systemization solution" refers to the optimal methods and technical proposals for systematizing specific business processes.

[0437] "Programming methods" refer to the specific coding procedures and techniques used to build computer systems.

[0438] This invention is a system that automatically automates the analysis of work procedure manuals to improve efficiency. Specifically, it consists of the following means.

[0439] First, the user uploads the work procedure manual file from their terminal to the server. This upload is done via an HTML form or a file upload API. The user selects the work procedure manual file (e.g., PDF, Word, etc.) and submits it by clicking the "Upload" button.

[0440] Next, the server analyzes the contents of the uploaded business procedure manual. This analysis uses Apache Tika to convert the file into text data and then uses Python's natural language processing module (e.g., NLTK, spaCy) to identify elements such as business procedures, roles, triggers, and conditions. In this process, business processes and elements are identified and extracted.

[0441] Next, the server generates a requirements definition diagram based on the extracted information. A flowchart generation library (e.g., Graphviz, PlantUML) is used to create a visual requirements definition diagram. This requirements definition diagram is in a user-friendly format, and the server displays this diagram to the user through a web interface.

[0442] From the displayed requirements diagram, the user selects the parts they want to automate. This selection is made by clicking on the requirements diagram, and the selection data is sent from the terminal to the server. The server performs a detailed analysis of the selected parts and uses a natural language processing module again to identify specific procedures and necessary resources. The analysis results are generated as detailed flowcharts and data flow diagrams and provided to the user.

[0443] Furthermore, the server compares the manual work procedures with the systemized processes and calculates the time savings using statistical algorithms. This calculation uses tools such as Python's pandas and scikit-learn, and the results are visualized and presented to the user as graphs and charts. For example, it might show a specific effect such as, "Systematizing the inventory update process can reduce time by 50%."

[0444] Finally, the server proposes the optimal systemization solution based on the analysis results and user requirements. This may include specific software frameworks (e.g., Django, Flask) and API combinations. The server also automatically generates specific programming methods and provides the user with sample code and programming instructions, allowing the user to proceed with implementation.

[0445] Specific example: Systematization of product inventory management

[0446] For example, if a user uploads a business procedure manual for "product inventory management," the system will operate as follows:

[0447] 1. The user uploads a product inventory management procedure file from their terminal to the server.

[0448] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[0449] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[0450] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[0451] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[0452] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[0453] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[0454] Examples of prompts to input into a generative AI model

[0455] When inputting a specific example of what happens when a user uploads a "Product Inventory Management Procedure Manual" into the AI ​​model, use the following prompt message:

[0456] The user uploaded a business procedure manual for product inventory management from their terminal to the server. The server analyzed the manual, extracted business processes such as "order taking," "procurement," and "inventory updating," and displayed an automatically generated requirements definition diagram to the user. The user chose to automate the "inventory updating process," and the server generated a detailed flowchart and provided it to the user. It was calculated that this would reduce the time required by 50% compared to the traditional manual process, and this result was presented to the user. Finally, the server proposed a solution using the "inventory module of the ERP system" and provided the user with program examples, including specific API call codes.

[0457] According to the embodiment for carrying out this invention, the process from uploading work procedure manuals to systemization and calculation of time-saving effects is efficiently executed.

[0458] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0459] Step 1: Upload the operational procedures manual.

[0460] The user uploads the work procedure manual file from their terminal to the server. The user selects the file using the browser's file upload function and clicks the "Upload" button. The input file can be in formats such as PDF or Word, and the output is a file saved on the server. This process imports the work procedure manual to the server.

[0461] Step 2: Analysis of operational procedures

[0462] The server analyzes the uploaded business procedure manuals. First, the server uses the Apache Tika library to convert the files into text data. The converted text is then analyzed using a natural language processing module (e.g., NLTK or spaCy) to identify elements such as business procedures, roles, triggers, and conditions. The input is text data, and the output is the result of extracting business processes and elements. Specifically, business processes such as "order taking," "inventory check," and "shipping preparation" are identified.

[0463] Step 3: Generating the Requirements Definition Diagram

[0464] The server generates a requirements definition diagram based on the extracted business processes and elements. The server creates a visual flowchart using a flowchart generation library (e.g., Graphviz or PlantUML). This flowchart shows the flow of the business process and is displayed in an easy-to-understand format for the user. The input is the extracted business process results, and the output is the generated requirements definition diagram. The requirements definition diagram is displayed to the user via a browser.

[0465] Step 4: Selecting the parts to be systematized

[0466] The user selects the parts they want to automate from the generated requirements diagram. The user makes this selection by clicking on the business processes they want to automate within the requirements diagram. The input is the requirements diagram, and the output is the data for the selected parts to be automated. This data is sent from the terminal to the server.

[0467] Step 5: Detailed analysis of the systemized portion

[0468] The server performs a detailed analysis of the systemization portion selected by the user. Using a natural language processing module again, it identifies the corresponding specific steps and required resources for the selected portion. The input is the data of the selected systemization portion, and the output is a detailed flowchart or data flow diagram. The analysis results are displayed to the user using a visualization tool (e.g., D3.js).

[0469] Step 6: Calculating the time-saving effect

[0470] The server compares the contents of the work procedure manual with the systematized process and calculates the time reduction effect using a statistical algorithm. The server analyzes the data using Python's pandas and scikit-learn to calculate how much work time is reduced by the systematization. The input is the analysis results of the work procedure manual and the process data after systematization, and the output is a report on the time reduction effect. The calculation results are presented to the user as a graph.

[0471] Step 7: Provide systemization solutions and programming methods.

[0472] The server proposes the optimal systemization solution based on the analysis results and user requirements. The server suggests specific software frameworks (e.g., Django, Flask) and API combinations, and automatically generates concrete programming instructions. The input is the analysis results and user selections, and the output is the proposed systemization solution and program examples. The generated program examples and procedures are provided to the user via a web interface.

[0473] (Application Example 1)

[0474] 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 glasses 214 will be referred to as the "terminal."

[0475] Traditional process for systematizing operational manuals required significant time and effort, from manual analysis and requirements definition to system selection and provision of programming methods. Furthermore, in environments demanding high efficiency, such as logistics centers, efficient work instructions and real-time procedure verification based on operational manuals were difficult, often leading to delays and errors. In particular, product inspection and inventory management required employees to memorize numerous procedures, which reduced work efficiency. There is a need to solve these problems and improve operational efficiency and accuracy.

[0476] 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.

[0477] In this invention, the server includes means for uploading business manual files, means for analyzing the contents of the uploaded business manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting parts to be systematized from the requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a visualization tool, means for comparing the business manual with the systematized process and calculating the time reduction effect, means for providing a systematization solution and a specific program, and means for displaying business procedures on smart glasses and instructing the next step via voice control. This automates and streamlines the systematization process of business manuals, enabling real-time display of appropriate procedures and voice-controlled next instructions, particularly in product inspection and inventory work at logistics centers.

[0478] "A means of uploading business manual files" refers to a mechanism for users to transfer document files containing procedures and rules related to their work to a server.

[0479] "A means of analyzing the contents of uploaded business manuals and extracting business processes and elements" refers to a system in which the server reads the contents of the received business manuals as digital data and uses natural language processing technology to identify elements such as business procedures and roles.

[0480] "A means of generating requirements definition diagrams based on extracted information" refers to a mechanism for creating visual flowcharts based on analyzed business flows and elements.

[0481] "A means of selecting the parts to be systematized from the requirements definition diagram" refers to a mechanism that allows users to review the generated requirements definition diagram and select the specific business processes they want to systematize.

[0482] "A means of analyzing the detailed requirements of the selected portion and displaying them with a visualization tool" refers to a system that further analyzes the business portion selected by the user and graphically displays the analysis results to the user.

[0483] "A method for comparing business manuals with systemized processes and calculating time savings" refers to a mechanism that compares traditional business procedures with systemized procedures and uses statistical algorithms to calculate how much time is saved after systemization.

[0484] "Means of providing systemized solutions and specific programs" refers to a mechanism that provides users with solutions utilizing specific software frameworks and APIs, as well as specific methods for their implementation, in order to improve the efficiency of business operations.

[0485] "A means of displaying work procedures on smart glasses and instructing the next step via voice control" refers to a system that uses the display of smart glasses to show work procedures and utilizes voice recognition functionality to instruct the next step in response to the worker's commands.

[0486] This invention is a system for improving the efficiency of product inspection and inventory management in logistics centers. The system's program processing and the hardware and software used are described in detail below.

[0487] The server first accepts user uploads of business manual files. To analyze the contents of the business manual, OCR (Optical Character Recognition) technology is used to convert it into text data, and then a natural language processing module (e.g., SpaCy, NLTK) is used. This allows elements such as business procedures, roles, triggers, and conditions to be extracted.

[0488] Based on the extracted information, the server generates a requirements definition diagram. This diagram is created using a flowchart generation library (e.g., Graphviz) and visually represents the business process. The generated requirements definition diagram is displayed on the user's terminal via a web interface.

[0489] Next, the user reviews the requirements definition diagram and selects the specific parts they want to automate. A detailed analysis of the selected parts is then performed, and the results are visualized in detail using a visualization tool (e.g., D3.js). This allows the user to understand the details of the business processes of the selected parts.

[0490] The server also compares the operational manual with the systemized process and calculates the time-saving effect. Using statistical algorithms, it calculates how much work time will be reduced by systemization and presents the results to the user.

[0491] Furthermore, the server provides optimal systemization solutions and specific programming methods based on the analysis results and user requirements. This includes the use of specific software frameworks and APIs.

[0492] Employees at the logistics center wear smart glasses (e.g., Google Glass, Vuzix) and perform their tasks while checking the work procedures displayed on the glasses. The smart glasses accept the next instruction using voice recognition, which allows them to display appropriate work instructions in real time.

[0493] Specific example

[0494] For example, when employees perform product inspection work at a logistics center, they wear smart glasses. The glasses display instructions such as "Please scan the product," and when they say "next" via voice prompt, the next step, "Please check the condition of the product," is displayed. This allows employees to work efficiently while confirming the steps.

[0495] Example of a prompt

[0496] "Upload the operational manual and use OCR and natural language processing to extract the operational procedures. Display the extracted procedures on smart glasses and use voice recognition to detect the next instruction and proceed to the next step."

[0497] In this way, this invention automates everything from the analysis of operational manuals to the systemization process, resulting in a significant improvement in operational efficiency at logistics centers.

[0498] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0499] Step 1:

[0500] The user uploads a work manual file from their terminal to the server. When the user selects the work manual file from their terminal and presses the "Upload" button, the file is transferred to the server. In this process, the input is the work manual file, and the output is the file being saved on the server.

[0501] Step 2:

[0502] The server analyzes the content of the uploaded business manuals and extracts business processes and elements. First, the server uses OCR technology to convert the business manuals into text data. Next, it uses a natural language processing module (e.g., SpaCy, NLTK) to identify business procedures, roles, triggers, and conditions. In this process, the input is text data, and the output is the extracted business processes and elements. Specifically, the OCR module analyzes image data, and the natural language processing module analyzes text to identify specific elements.

[0503] Step 3:

[0504] Based on the extracted information, the server generates a requirements definition diagram. This is done using a flowchart generation library (e.g., Graphviz). The input is the extracted business processes and elements, and the output is a visual requirements definition diagram. The server converts the flow of business processes into a diagram using the library and presents it in a user-friendly format.

[0505] Step 4:

[0506] The user selects the parts they want to automate from the requirements diagram. The server displays the requirements diagram via a web interface, allowing the user to select the parts they want to automate using mouse clicks or taps. The input is the entire requirements diagram, and the output is the data for the parts selected by the user. The server accepts user input and understands the selected parts.

[0507] Step 5:

[0508] The server analyzes the detailed requirements of the selected portion and displays them using a visualization tool (e.g., D3.js). It analyzes the selected data in detail and displays the results graphically. The input is the data of the selected business portion, and the output is a visualization of the detailed analysis results. Specifically, it analyzes the selected data in detail and depicts the analysis results as a diagram.

[0509] Step 6:

[0510] The server compares the contents of the operational manual with the systemized process and calculates the time reduction effect. A statistical algorithm is used for this calculation. Inputs include analysis results and data on the systemized process, while output is a specific numerical value regarding the time reduction effect. The comparison algorithm is used to process the data and calculate the time reduction effect.

[0511] Step 7:

[0512] The server provides systemization solutions and specific programming methods. This includes the use of specific software frameworks and APIs. Inputs are analysis results and user requirements, while outputs are recommended solutions and specific programming methods. Based on the analysis data, the server selects the optimal solution and generates specific program examples.

[0513] Step 8:

[0514] The smart glasses display work procedures and provide voice commands to guide the user to the next step. The smart glasses' display shows the work procedures, and voice recognition (e.g., Google Speech-to-Text) is used to accept the next instruction. Input consists of work procedures and voice commands, while output is a display of the next step. Specifically, the smart glasses display the next step based on the voice command they detect.

[0515] 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.

[0516] This invention relates to a system that automates and streamlines the process from analyzing business manuals to systematizing them. This system incorporates an emotion engine that recognizes user emotions and has the function to adjust the interface and provide support according to the user's emotional state. The program processing of this system is described below in natural language.

[0517] Uploading and analyzing business manuals

[0518] The user uploads the work manual file from their terminal to the server. The user uses the terminal's web interface to select the work manual file and clicks the upload button. The terminal then sends the selected file to the server.

[0519] The server receives the uploaded business manual content and begins analysis. The server converts the file content into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This allows for the extraction of business processes and elements.

[0520] Generation of Requirements Definition Diagrams

[0521] The server automatically generates a requirements definition diagram based on the extracted business processes and elements. The requirements definition diagram visually represents the flow of business processes and is provided in a format that is easy for the user to understand. The server uses a flowchart generation library to create a visual requirements definition diagram and displays it to the user through a web interface.

[0522] Selection and analysis of the systematization components

[0523] Users can select the parts they want to automate from the generated requirements definition diagram. The selected data is sent from the terminal to the server, which then performs a detailed analysis of those parts. The analysis results are displayed to the user using a detailed visualization tool. This allows the user to understand the details of the specific business processes to be automated.

[0524] Calculation of time-saving effect

[0525] The server compares the contents of the operational manual with the systematized process and calculates the time savings. This calculation uses a statistical algorithm to specifically show how much work time is saved through systemization. The calculation results are visualized and presented to the user.

[0526] Providing system solutions and programming methods.

[0527] Based on the analysis results and user requirements, the server proposes the optimal systemization solution. This may include specific software frameworks and API combinations. Furthermore, the server automatically generates specific programming methods and provides them to the user. The provided programming methods include sample code and programming procedures, allowing the user to proceed with implementation based on these.

[0528] Utilizing the Emotion Engine

[0529] During user interaction, the emotion engine recognizes the user's emotional state. This emotion engine analyzes the user's emotions through voice and text analysis. Based on the analysis results, the server adjusts the interface according to the user's emotional state. For example, if the user is feeling confused or frustrated, the system will adjust to provide more detailed explanations and guidance. Support messages and guidance will also be provided according to the user's emotional state.

[0530] Specific example: Systematization of product inventory management

[0531] For example, if a user uploads a business manual for "product inventory management," the system will operate as follows:

[0532] 1. The user uploads the product inventory management manual file from their terminal to the server.

[0533] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[0534] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[0535] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[0536] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[0537] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[0538] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[0539] 8. The emotion engine analyzes the user's emotions from their voice and text, and if the user is confused, the system adjusts the interface to provide more detailed explanations or additional guidance.

[0540] This allows users to smoothly define requirements based on operational manuals and achieve efficient system implementation. The use of an emotion engine improves the user experience, leading to further efficiency improvements and increased user satisfaction.

[0541] The following describes the processing flow.

[0542] Step 1:

[0543] The user uploads the work manual file from their terminal to the server. The user selects the work manual file through the terminal's web interface and clicks the upload button. The terminal then sends the selected file to the server.

[0544] Step 2:

[0545] The server receives the uploaded business manual and begins analysis. The server converts the file contents into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This extracts the business processes and elements.

[0546] Step 3:

[0547] The server generates a requirements definition diagram based on the extracted information. The server uses a flowchart generation library to automatically generate flowcharts of business processes. The generated requirements definition diagram is displayed to the user through a web interface in a visually easy-to-understand format.

[0548] Step 4:

[0549] The user selects the parts they want to automate from the generated requirements diagram. The user reviews the requirements diagram and clicks to select the parts they wish to automate. The terminal sends the data for the selected parts to the server.

[0550] Step 5:

[0551] The server performs a detailed analysis of the selected portion. Based on the received data, the server performs a detailed analysis of the selected business process. The server uses detailed visualization tools to generate the analysis results as visual flowcharts and ER diagrams, which are then displayed to the user.

[0552] Step 6:

[0553] The server compares the contents of the operational manual with the process after systemization and calculates the time savings. The server uses a statistical algorithm to calculate the time saved by systemization. The calculation results are visualized and presented to the user.

[0554] Step 7:

[0555] The server provides the optimal systemization solution and specific programming methods. Based on the analysis results and user requirements, the server selects the optimal systemization solution (such as a combination of specific software frameworks and APIs). Furthermore, the server automatically generates sample code and programming instructions and provides them to the user.

[0556] Step 8:

[0557] The emotion engine recognizes the user's emotional state. The terminal and server collect the user's emotions through voice or text input, and the emotion engine analyzes this data. Based on the analysis results, the server adjusts the interface according to the user's emotional state. For example, if the user is confused, the server provides detailed explanations or additional guidance.

[0558] Specific example: Systematization of product inventory management

[0559] Step 1:

[0560] The user uploads the "Product Inventory Management" business manual file to the server using a terminal.

[0561] Step 2:

[0562] The server receives the uploaded manual, converts it into text data, applies a natural language processing module, and extracts business processes such as "order placement," "procurement," and "inventory update."

[0563] Step 3:

[0564] The server generates a requirements definition diagram based on the extracted information and displays this diagram, including the "flow from order placement to inventory update," to the user.

[0565] Step 4:

[0566] The user reviews the requirements diagram and selects to automate the "inventory update process." The terminal then sends the selected data to the server.

[0567] Step 5:

[0568] The server analyzes the details of the "inventory update process," generates a detailed flowchart, and displays it to the user.

[0569] Step 6:

[0570] The server calculates the time saved by systematizing the inventory update process and presents to the user that a 50% time reduction is possible compared to the traditional manual process.

[0571] Step 7:

[0572] The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, including specific API call code.

[0573] Step 8:

[0574] The emotion engine analyzes the user's emotions from their voice and text, and if the user appears confused, the server adjusts the interface to provide more detailed explanations and additional guidance.

[0575] (Example 2)

[0576] 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".

[0577] Automating the entire process, from analyzing existing business manuals and generating requirements definition diagrams to implementing systems and improving operational efficiency, is challenging. Furthermore, to enhance the user experience, it's necessary to accurately recognize the user's emotional state during operation and for the system to respond appropriately accordingly. A system is needed that can efficiently and appropriately address these challenges.

[0578] 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.

[0579] In this invention, the server includes means for uploading electronic files of business manuals, means for analyzing the contents of the uploaded business manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting parts to be systematized from the generated requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a detailed visualization tool, means for comparing the business manual with the systematized process and calculating the time reduction effect using statistical methods, means for providing a systematization solution and specific programming methods, and means including an emotion engine that adjusts the interface based on the user's emotional state. As a result, the process from business manual analysis to systematization is automated, enabling improved user experience and a significant increase in business efficiency.

[0580] A "business manual" is a document that outlines work procedures, roles, rules, and other information within a company or organization.

[0581] An "electronic file" is a digital document or data file that can be handled by a computer.

[0582] "Uploading" refers to the act of transferring data or files from a user's device to a server or cloud storage.

[0583] A "natural language processing module" is software or an algorithm that analyzes natural language data, such as text and speech, to extract and understand its meaning.

[0584] A "business process" is a set of steps and activities necessary to complete a specific task.

[0585] A "requirements definition diagram" is a diagram that visually represents business processes and elements, and serves as the foundation for system development.

[0586] A "visualization tool" is software used to visually display and analyze data and information.

[0587] A "statistical algorithm" refers to statistical methods and calculation procedures used for data analysis and prediction.

[0588] A "systemization solution" refers to specific technical measures or proposals aimed at automating and streamlining business processes.

[0589] "Programming method" refers to the way a program is written or the procedures involved in achieving a specific task or solution.

[0590] An "emotion engine" is software or a system that analyzes a user's emotional state in real time and provides appropriate feedback and interface adjustments.

[0591] This invention relates to a system that automates and streamlines the process from analyzing business manuals to systematizing them. This system incorporates an emotion engine that recognizes the user's emotional state and has functions to adjust the interface and provide support.

[0592] Uploading and analyzing business manuals

[0593] The user uploads an electronic file of the work manual from their terminal to the server. The user uses the terminal's web interface to select the work manual file and clicks the upload button. The terminal sends the selected file to the server via an HTTP POST request. The server parses the received file and converts it into text data. This parsing is performed using a natural language processing module (e.g., spaCy or NLTK) to identify elements such as work procedures, roles, triggers, and conditions.

[0594] Generation of Requirements Definition Diagrams

[0595] The server generates a requirements definition diagram using a flowchart drawing library (e.g., Graphviz) based on the extracted business processes and elements. The requirements definition diagram is displayed to the user via a web interface, allowing the user to visually understand the business processes.

[0596] Selection and analysis of the systematization components

[0597] The user selects the part of the requirements diagram they want to automate via a web interface. For example, the user selects the "Inventory Update" process by clicking on it. The selected data is sent from the terminal to the server, which then performs a detailed analysis of that part. The analysis results are displayed to the user using a detailed visualization tool (e.g., D3.js).

[0598] Calculation of time-saving effect

[0599] The server compares the contents of the operational manual with the systematized process and calculates the time savings. This calculation uses a statistical algorithm (e.g., Scikit-learn in Python) to specifically demonstrate the time savings achieved through systematization. The calculation results are visualized and presented to the user.

[0600] Providing system solutions and programming methods.

[0601] Based on the analysis results and user requirements, the server proposes an appropriate systemization solution. For example, it might suggest "using the inventory module of an ERP system." This proposal would also include appropriate frameworks and APIs (e.g., Django or Flask). The server provides specific programming methods and offers sample code and programming instructions to help the user implement the solution.

[0602] Utilizing the Emotion Engine

[0603] While the user is interacting with the system, an emotion engine recognizes the user's emotional state. This emotion engine analyzes the user's emotions through speech analysis (e.g., Google Speech-to-Text API) and text analysis (e.g., OpenAI's GPT). Based on the analysis results, the server adjusts the interface according to the user's emotional state. For example, if the user is feeling confused or frustrated, the system will adjust to provide detailed explanations and guidance.

[0604] Specific example: Systematization of product inventory management

[0605] For example, if a user uploads a business manual for "product inventory management," the system will operate as follows:

[0606] 1. The user uploads the product inventory management manual file from their terminal to the server.

[0607] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[0608] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[0609] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[0610] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[0611] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[0612] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[0613] 8. The emotion engine analyzes the user's emotions from their voice and text, and if the user is confused, the system adjusts the interface to provide more detailed explanations or additional guidance.

[0614] Example of a prompt

[0615] "Please upload the product inventory management operations manual, generate a requirements definition diagram, and systematize the inventory update process."

[0616] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0617] Step 1: Select and upload the business manual file.

[0618] The user uploads an electronic file of the work manual from their terminal to the server. The user uses the terminal's web interface to click the "Select File" button and chooses the work manual file. This action sends the selected file to the server when the user clicks the upload button. The server receives the HTTP POST request and stores the work manual file. Here, the input is the electronic file of the work manual selected by the user, and the output is the file stored on the server.

[0619] Step 2: Analyze the contents of the operational manual

[0620] The server analyzes the received business manual file. First, the server converts the file into text data, and then uses a natural language processing module (e.g., spaCy or NLTK) to identify elements such as business procedures, roles, triggers, and conditions. The input here is the text data of the business manual stored on the server, and the output is the extracted elements such as business procedures and roles. Specifically, the process involves analyzing the text content, extracting keywords and phrases, and converting it into structured data.

[0621] Step 3: Generating the Requirements Definition Diagram

[0622] The server generates a requirements definition diagram using a flowchart drawing library (e.g., Graphviz) based on the extracted business processes and elements. The generated requirements definition diagram is displayed to the user via a web interface. The input here is the extracted business processes and elements, and the output is the requirements definition diagram. Specifically, the operation involves converting the extracted data into a visual flowchart and displaying it in a user-friendly format.

[0623] Step 4: Selecting the parts to be systematized

[0624] The user selects the part of the requirements diagram they want to automate via a web interface. For example, clicking on the "Inventory Update" process selects that part. The selected data is sent from the terminal to the server. The input here is the part of the requirements diagram selected by the user, and the output is the selected data sent to the server. Specifically, the operation involves clicking on a particular part of the interface to select the part to be automated.

[0625] Step 5: Detailed Analysis and Visualization

[0626] The server performs a detailed analysis of the selected portion and displays it to the user using a detailed visualization tool (e.g., D3.js). The input here is a portion of the requirements diagram selected by the user, and the output is the detailed analysis results and their visualization data. Specific operations include data analysis of the selected portion, generation of a detailed flowchart, and display on the interface.

[0627] Step 6: Calculating the time-saving effect

[0628] The server compares the contents of the work manual with the systematized process and calculates the time savings. This calculation uses a statistical algorithm (e.g., Scikit-learn in Python). The input is the analysis results of the work manual and the data of the systematized process, and the output is the calculated time savings. The specific operation includes comparing the time required for manual and systematized tasks, calculating the effect using statistical methods, and visualizing the results.

[0629] Step 7: Provide systemization solutions and programming methods.

[0630] The server proposes the optimal systemization solution based on the analysis results and user requirements. For example, it might suggest "using the inventory module of the ERP system." It also provides specific programming methods (code examples and programming procedures). The input here is the analysis results and user requirements, while the output is the proposed solution and programming method. Specific operations include evaluating the analysis results, selecting an appropriate solution, and providing specific programming procedures.

[0631] Step 8: Utilizing the Emotional Engine

[0632] While the user is interacting with the system, the emotion engine recognizes the user's emotional state and adjusts the interface accordingly. This emotion engine uses speech analysis (e.g., Google Speech-to-Text API) and text analysis (e.g., OpenAI's GPT). The input is the user's voice or text data, and the output is the emotion analysis results and the adjusted interface. Specific operations include real-time analysis of the user's voice and text, identification of emotional state, and dynamic adjustment of the interface.

[0633] (Application Example 2)

[0634] 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."

[0635] Traditional systemization processes based on operational manuals require manual analysis and requirements definition, which are extremely time-consuming and labor-intensive. This results in decreased productivity and makes it difficult to improve operational efficiency. Furthermore, the inability to adjust the interface and provide support based on user emotions makes it difficult to improve the user experience.

[0636] 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.

[0637] In this invention, the server includes means for uploading business manual files, means for analyzing the contents of the uploaded business manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting parts to be systematized from the requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a visualization tool, means for comparing the business manual with the systematized process and calculating the time reduction effect, means for providing a systematization solution and specific programming methods, and means for adjusting the interface and support according to the user's emotional state using an emotion engine that recognizes the user's emotions. As a result, the analysis and systematization of business manuals are automated, significantly reducing labor and time, while enabling flexible support that responds to the user's emotions.

[0638] A "business manual" is a document that contains detailed explanations of specific business procedures, roles, triggers, and conditions.

[0639] "Method of uploading" refers to the function or interface that allows users to send work manual files from their terminal to the server.

[0640] The "means of analysis" refer to a function that converts the content of uploaded business manuals into text data and extracts business processes and elements using natural language processing technology.

[0641] A "requirements definition diagram" is a diagram that visually represents the flow and process of business operations, making it easy for users to understand.

[0642] "Systematizing" refers to automating business processes that were previously performed manually and improving efficiency through the use of software and systems.

[0643] A "visualization tool" is a tool or interface used to visually display analyzed data or process flows.

[0644] "Time-saving effect" refers to the amount of time saved by systematizing tasks compared to traditional manual processes.

[0645] A "systemization solution" refers to a combination of software frameworks and APIs optimized for automating specific business processes.

[0646] "Programming method" refers to the implementation method of a program, including specific procedures and sample code for systemization.

[0647] An "emotion engine" is a technology that recognizes a user's emotional state through voice and text analysis, and adjusts the interface and support based on the results.

[0648] An "interface" refers to the screen display and means of operation that a user uses to interact with a system.

[0649] "Support" refers to the guidance and supplementary information provided to users when using a system.

[0650] This invention aims to efficiently systematize operations based on the operation manuals for robots used in factories. In particular, it describes a system that provides information to the user visually using smart glasses and provides support tailored to the user's state using an emotion engine.

[0651] Uploading and analyzing business manuals

[0652] First, the user uploads the robot operation manual from their device to the server via smart glasses. Using the smart glasses' user interface, they select the manual file and send it to the cloud server. The server receives the uploaded manual and converts it into text data. The software used here includes a natural language processing (NLP) module, which extracts work procedures, roles, and other relevant information.

[0653] Generation of Requirements Definition Diagrams

[0654] The server automatically generates a requirements definition diagram based on the extracted business processes and elements. This process uses a flowchart generation library to visually represent the business flow. The generated requirements definition diagram is displayed on the smart glasses screen.

[0655] Selection and analysis of the systematization components

[0656] Users select the parts they want to systemize from a requirements definition diagram using smart glasses. The selected data is sent from the terminal to the server, which then performs a detailed analysis of that part. During this process, a detailed process flow is displayed using a visualization tool.

[0657] Calculation of time-saving effect

[0658] The server compares the contents of the operational manual with the systematized process and calculates the time-saving effect using a statistical algorithm. The calculation results are visualized and presented to the user.

[0659] Providing system solutions and programming methods.

[0660] Furthermore, the server proposes the optimal systemization solution based on the analysis results and user selections. This includes specific software frameworks, API usage methods, and sample code. This enables efficient implementation.

[0661] Utilizing the Emotion Engine

[0662] When a user uses smart glasses, the emotion engine recognizes the user's emotional state through voice and text analysis. For example, if the user is confused, the system provides a detailed explanation. The interface is also adjusted and support messages are provided according to the emotional state.

[0663] Specific example

[0664] For example, a new factory operator uploads a robot initial setup manual to smart glasses. The system extracts the robot operation procedures and generates an initial setup flowchart. The operator follows the flowchart displayed on the smart glasses, performing the operations step by step. If there are any questions, the glasses' emotion engine detects the operator's confusion and automatically displays detailed explanations or video tutorials. This allows even inexperienced operators to set up the robot with confidence.

[0665] Example of a prompt

[0666] Please describe the entire process of a system that automatically generates requirements definition diagrams from factory robot operation manuals and displays them to users using smart glasses, and provide a concrete example of how to use an emotion engine for user support.

[0667] This invention automates the analysis and systematization of business manuals, resulting in a significant reduction in labor and time, while also enabling flexible support tailored to the user's needs.

[0668] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0669] Step 1:

[0670] Uploading the business manual

[0671] The user selects a robot operation manual file using the user interface of the smart glasses and presses the upload button. This sends the selected manual file from the terminal (smart glasses) to the server.

[0672] Input: Business manual file

[0673] Output: Business manual file uploaded to the server

[0674] Step 2:

[0675] Analysis of business manuals

[0676] The server receives the uploaded business manual file and converts its contents into text data. A natural language processing (NLP) module is used to extract business processes and elements (procedures, roles, triggers, conditions, etc.).

[0677] Input: Uploaded business manual file

[0678] Output: Extracted business processes and elements

[0679] Step 3:

[0680] Generation of Requirements Definition Diagrams

[0681] The server uses a flowchart generation library to automatically generate requirements definition diagrams based on the extracted business processes and elements. The generated requirements definition diagrams are saved in the cloud and displayed on smart glasses.

[0682] Input: Extracted business processes and elements

[0683] Output: Requirements definition diagram

[0684] Step 4:

[0685] Selection of Systematization Components

[0686] The user selects the parts of the requirements diagram they want to automate through the display interface of their smart glasses. The selected data is then sent from the device to the server.

[0687] Input: Requirements definition diagram

[0688] Output: Selected systemization portion

[0689] Step 5:

[0690] Detailed analysis and visualization

[0691] The server analyzes the selected system components in detail and generates a detailed process flow. The generated flow is then displayed to the user in an easy-to-understand format using a visualization tool.

[0692] Input: Selected systemization portion

[0693] Output: Detailed process flow

[0694] Step 6:

[0695] Calculation of time-saving effect

[0696] The server compares the contents of the operational manual with the systematized process and uses a statistical algorithm to calculate the time savings. The calculation results are visualized and displayed on smart glasses.

[0697] Input: Detailed process flow

[0698] Output: Calculation results of time reduction effect

[0699] Step 7:

[0700] Providing system solutions and programming methods.

[0701] The server proposes the optimal systemization solution based on the analysis results and user requests. Furthermore, it provides specific program sample code and instructions on how to use the API.

[0702] Input: Calculation result of time reduction effect

[0703] Output: Systematized solution and specific program steps

[0704] Step 8:

[0705] Utilizing the Emotion Engine

[0706] When a user uses smart glasses, the emotion engine recognizes the user's emotional state through voice analysis and eye tracking. For example, if the user is confused, the system displays a detailed explanation or video tutorial.

[0707] Input: User sentiment data

[0708] Output: Interface adjustments and support information tailored to user sentiment.

[0709] 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.

[0710] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0711] 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.

[0712] [Third Embodiment]

[0713] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0714] 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.

[0715] 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).

[0716] 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.

[0717] 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.

[0718] 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).

[0719] 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.

[0720] 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.

[0721] 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.

[0722] 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.

[0723] 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.

[0724] 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".

[0725] This invention relates to a system that automates and streamlines the process from analyzing business manuals to systematizing them. The program processing of this system is described below in natural language.

[0726] Uploading and analyzing business manuals

[0727] The user uploads a business manual file from their terminal to the server. The server receives this file and begins analysis. Specifically, the server converts the file's contents into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This allows for the extraction of business processes and elements.

[0728] Generation of Requirements Definition Diagrams

[0729] The server automatically generates a requirements definition diagram based on the extracted business processes and elements. The requirements definition diagram visually represents the flow of business processes and is provided in a format that is easy for the user to understand. The server uses a flowchart generation library to create a visual requirements definition diagram and displays it to the user through a web interface.

[0730] Selection and analysis of the systematization components

[0731] Users can select the parts they want to automate from the generated requirements definition diagram. The selected data is sent from the terminal to the server, which then performs a detailed analysis of those parts. The analysis results are displayed to the user using a detailed visualization tool. This allows the user to understand the details of the specific business processes to be automated.

[0732] Calculation of time-saving effect

[0733] The server compares the contents of the operational manual with the systematized process and calculates the time savings. This calculation uses a statistical algorithm to specifically show how much work time is saved through systemization. The calculation results are visualized and presented to the user.

[0734] Providing system solutions and programming methods.

[0735] Based on the analysis results and user requirements, the server proposes the optimal systemization solution. This may include specific software frameworks and API combinations. Furthermore, the server automatically generates specific programming methods and provides them to the user. The provided programming methods include sample code and programming procedures, allowing the user to proceed with implementation based on these.

[0736] Specific example: Systematization of product inventory management

[0737] For example, if a user uploads a business manual for "product inventory management," the system will operate as follows:

[0738] 1. The user uploads the product inventory management manual file from their terminal to the server.

[0739] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[0740] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[0741] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[0742] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[0743] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[0744] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[0745] This allows users to smoothly define requirements based on business manuals and achieve efficient system implementation.

[0746] The following describes the processing flow.

[0747] Step 1:

[0748] The user uploads the work manual file from their terminal to the server. The user uses the terminal's web interface to select the work manual file and clicks the upload button. The terminal then sends the selected file to the server.

[0749] Step 2:

[0750] The server receives the uploaded business manual and begins analysis. The server converts the file contents into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This allows for the extraction of business processes and elements.

[0751] Step 3:

[0752] The server generates a requirements definition diagram based on the extracted information. The server analyzes the business process flow and uses a flowchart generation library to create a visual requirements definition diagram. The server displays the generated requirements definition diagram to the user through a web interface.

[0753] Step 4:

[0754] The user selects the parts they want to automate from the requirements diagram. The user reviews the displayed requirements diagram and clicks to select the parts they want to automate. The terminal sends the selected data to the server.

[0755] Step 5:

[0756] The server performs a detailed analysis of the selected portion. Based on the received data, the server performs a detailed analysis of the selected business process and generates detailed visualizations (flowcharts and ER diagrams). The server displays the generated diagrams to the user via a web interface.

[0757] Step 6:

[0758] The server compares the contents of the operational manual with the process after systemization and calculates the time savings. The server uses statistical algorithms to calculate the time saved by systemization. The calculation results are visualized and presented to the user.

[0759] Step 7:

[0760] The server provides the optimal systemization solution and specific programming methods. Based on the analysis results and user requirements, the server selects the appropriate systemization solution and automatically generates sample code and programming procedures. The server then presents this to the user through a web interface.

[0761] The above describes the detailed flow of program processing in the "RequirementsCraft" system and the specific actions performed at each processing step.

[0762] (Example 1)

[0763] 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."

[0764] The requirements definition and system development associated with the systemization of traditional business processes were often manual, time-consuming, and labor-intensive. Furthermore, there were concerns about errors and decreased efficiency in the process of extracting systemization requirements from business manuals. Additionally, the effectiveness of systemization was difficult to evaluate concretely beforehand, making the post-implementation effects uncertain. This led to delays in systemization aimed at improving business efficiency.

[0765] 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.

[0766] In this invention, the server includes means for uploading business procedure manual files, means for analyzing the contents of the uploaded business procedure manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting the parts to be systematized from the requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a visualization tool, means for comparing the business procedure manuals with the systematized processes and calculating the time reduction effect, and means for providing systematization solutions and specific programming methods. This makes it possible to automatically extract systematization requirements from business manuals and efficiently build systems. Furthermore, by evaluating the effects of systematization in advance, concrete effects can be expected before implementation.

[0767] A "work procedure manual" is a document that describes work processes and procedures, clearly outlining how to perform the work, the roles involved, and the conditions.

[0768] "Uploading" refers to the action of sending a file from a device to a server, and means transmitting digital data over the internet.

[0769] "Analysis" refers to the process of analyzing the content of data or documents to extract specific information or patterns.

[0770] A "business process" refers to a series of business procedures or activities performed to achieve a specific objective.

[0771] An "element" is a specific item or part that makes up a business process, and includes procedures, roles, triggers, conditions, etc.

[0772] A "requirements definition diagram" is a diagram that visually represents the interrelationships between business processes and elements, showing the flow and relationships of business procedures.

[0773] "Systematization" refers to the introduction of computer systems to automate business processes that are currently performed manually.

[0774] "Selection" refers to the act of choosing a specific item from among multiple options.

[0775] "Detailed requirements" refers to the specific conditions and specifications necessary for system implementation.

[0776] A "visualization tool" is a software tool used to visually display data and information, and includes tools that generate graphs, charts, and flowcharts.

[0777] "Time-saving effect" refers to the effect of streamlining business processes through systemization, thereby reducing the time required.

[0778] A "statistical algorithm" refers to a mathematical method used to analyze data and derive statistical conclusions or predictions.

[0779] A "systemization solution" refers to the optimal methods and technical proposals for systematizing specific business processes.

[0780] "Programming methods" refer to the specific coding procedures and techniques used to build computer systems.

[0781] This invention is a system that automatically automates the analysis of work procedure manuals to improve efficiency. Specifically, it consists of the following means.

[0782] First, the user uploads the work procedure manual file from their terminal to the server. This upload is done via an HTML form or a file upload API. The user selects the work procedure manual file (e.g., PDF, Word, etc.) and submits it by clicking the "Upload" button.

[0783] Next, the server analyzes the contents of the uploaded business procedure manual. This analysis uses Apache Tika to convert the file into text data and then uses Python's natural language processing module (e.g., NLTK, spaCy) to identify elements such as business procedures, roles, triggers, and conditions. In this process, business processes and elements are identified and extracted.

[0784] Next, the server generates a requirements definition diagram based on the extracted information. A flowchart generation library (e.g., Graphviz, PlantUML) is used to create a visual requirements definition diagram. This requirements definition diagram is in a user-friendly format, and the server displays this diagram to the user through a web interface.

[0785] From the displayed requirements diagram, the user selects the parts they want to automate. This selection is made by clicking on the requirements diagram, and the selection data is sent from the terminal to the server. The server performs a detailed analysis of the selected parts and uses a natural language processing module again to identify specific procedures and necessary resources. The analysis results are generated as detailed flowcharts and data flow diagrams and provided to the user.

[0786] Furthermore, the server compares the manual work procedures with the systemized processes and calculates the time savings using statistical algorithms. This calculation uses tools such as Python's pandas and scikit-learn, and the results are visualized and presented to the user as graphs and charts. For example, it might show a specific effect such as, "Systematizing the inventory update process can reduce time by 50%."

[0787] Finally, the server proposes the optimal systemization solution based on the analysis results and user requirements. This may include specific software frameworks (e.g., Django, Flask) and API combinations. The server also automatically generates specific programming methods and provides the user with sample code and programming instructions, allowing the user to proceed with implementation.

[0788] Specific example: Systematization of product inventory management

[0789] For example, if a user uploads a business procedure manual for "product inventory management," the system will operate as follows:

[0790] 1. The user uploads a product inventory management procedure file from their terminal to the server.

[0791] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[0792] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[0793] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[0794] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[0795] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[0796] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[0797] Examples of prompts to input into a generative AI model

[0798] When inputting a specific example of what happens when a user uploads a "Product Inventory Management Procedure Manual" into the AI ​​model, use the following prompt message:

[0799] The user uploaded a business procedure manual for product inventory management from their terminal to the server. The server analyzed the manual, extracted business processes such as "order taking," "procurement," and "inventory updating," and displayed an automatically generated requirements definition diagram to the user. The user chose to automate the "inventory updating process," and the server generated a detailed flowchart and provided it to the user. It was calculated that this would reduce the time required by 50% compared to the traditional manual process, and this result was presented to the user. Finally, the server proposed a solution using the "inventory module of the ERP system" and provided the user with program examples, including specific API call codes.

[0800] According to the embodiment for carrying out this invention, the process from uploading work procedure manuals to systemization and calculation of time-saving effects is efficiently executed.

[0801] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0802] Step 1: Upload the operational procedures manual.

[0803] The user uploads the work procedure manual file from their terminal to the server. The user selects the file using the browser's file upload function and clicks the "Upload" button. The input file can be in formats such as PDF or Word, and the output is a file saved on the server. This process imports the work procedure manual to the server.

[0804] Step 2: Analysis of operational procedures

[0805] The server analyzes the uploaded business procedure manuals. First, the server uses the Apache Tika library to convert the files into text data. The converted text is then analyzed using a natural language processing module (e.g., NLTK or spaCy) to identify elements such as business procedures, roles, triggers, and conditions. The input is text data, and the output is the result of extracting business processes and elements. Specifically, business processes such as "order taking," "inventory check," and "shipping preparation" are identified.

[0806] Step 3: Generating the Requirements Definition Diagram

[0807] The server generates a requirements definition diagram based on the extracted business processes and elements. The server creates a visual flowchart using a flowchart generation library (e.g., Graphviz or PlantUML). This flowchart shows the flow of the business process and is displayed in an easy-to-understand format for the user. The input is the extracted business process results, and the output is the generated requirements definition diagram. The requirements definition diagram is displayed to the user via a browser.

[0808] Step 4: Selecting the parts to be systematized

[0809] The user selects the parts they want to automate from the generated requirements diagram. The user makes this selection by clicking on the business processes they want to automate within the requirements diagram. The input is the requirements diagram, and the output is the data for the selected parts to be automated. This data is sent from the terminal to the server.

[0810] Step 5: Detailed analysis of the systemized portion

[0811] The server performs a detailed analysis of the systemization portion selected by the user. Using a natural language processing module again, it identifies the corresponding specific steps and required resources for the selected portion. The input is the data of the selected systemization portion, and the output is a detailed flowchart or data flow diagram. The analysis results are displayed to the user using a visualization tool (e.g., D3.js).

[0812] Step 6: Calculating the time-saving effect

[0813] The server compares the contents of the work procedure manual with the systematized process and calculates the time reduction effect using a statistical algorithm. The server analyzes the data using Python's pandas and scikit-learn to calculate how much work time is reduced by the systematization. The input is the analysis results of the work procedure manual and the process data after systematization, and the output is a report on the time reduction effect. The calculation results are presented to the user as a graph.

[0814] Step 7: Provide systemization solutions and programming methods.

[0815] The server proposes the optimal systemization solution based on the analysis results and user requirements. The server suggests specific software frameworks (e.g., Django, Flask) and API combinations, and automatically generates concrete programming instructions. The input is the analysis results and user selections, and the output is the proposed systemization solution and program examples. The generated program examples and procedures are provided to the user via a web interface.

[0816] (Application Example 1)

[0817] 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."

[0818] Traditional process for systematizing operational manuals required significant time and effort, from manual analysis and requirements definition to system selection and provision of programming methods. Furthermore, in environments demanding high efficiency, such as logistics centers, efficient work instructions and real-time procedure verification based on operational manuals were difficult, often leading to delays and errors. In particular, product inspection and inventory management required employees to memorize numerous procedures, which reduced work efficiency. There is a need to solve these problems and improve operational efficiency and accuracy.

[0819] 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.

[0820] In this invention, the server includes means for uploading business manual files, means for analyzing the contents of the uploaded business manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting parts to be systematized from the requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a visualization tool, means for comparing the business manual with the systematized process and calculating the time reduction effect, means for providing a systematization solution and a specific program, and means for displaying business procedures on smart glasses and instructing the next step via voice control. This automates and streamlines the systematization process of business manuals, enabling real-time display of appropriate procedures and voice-controlled next instructions, particularly in product inspection and inventory work at logistics centers.

[0821] "A means of uploading business manual files" refers to a mechanism for users to transfer document files containing procedures and rules related to their work to a server.

[0822] "A means of analyzing the contents of uploaded business manuals and extracting business processes and elements" refers to a system in which the server reads the contents of the received business manuals as digital data and uses natural language processing technology to identify elements such as business procedures and roles.

[0823] "A means of generating requirements definition diagrams based on extracted information" refers to a mechanism for creating visual flowcharts based on analyzed business flows and elements.

[0824] "A means of selecting the parts to be systematized from the requirements definition diagram" refers to a mechanism that allows users to review the generated requirements definition diagram and select the specific business processes they want to systematize.

[0825] "A means of analyzing the detailed requirements of the selected portion and displaying them with a visualization tool" refers to a system that further analyzes the business portion selected by the user and graphically displays the analysis results to the user.

[0826] "A method for comparing business manuals with systemized processes and calculating time savings" refers to a mechanism that compares traditional business procedures with systemized procedures and uses statistical algorithms to calculate how much time is saved after systemization.

[0827] "Means of providing systemized solutions and specific programs" refers to a mechanism that provides users with solutions utilizing specific software frameworks and APIs, as well as specific methods for their implementation, in order to improve the efficiency of business operations.

[0828] "A means of displaying work procedures on smart glasses and instructing the next step via voice control" refers to a system that uses the display of smart glasses to show work procedures and utilizes voice recognition functionality to instruct the next step in response to the worker's commands.

[0829] This invention is a system for improving the efficiency of product inspection and inventory management in logistics centers. The system's program processing and the hardware and software used are described in detail below.

[0830] The server first accepts user uploads of business manual files. To analyze the contents of the business manual, OCR (Optical Character Recognition) technology is used to convert it into text data, and then a natural language processing module (e.g., SpaCy, NLTK) is used. This allows elements such as business procedures, roles, triggers, and conditions to be extracted.

[0831] Based on the extracted information, the server generates a requirements definition diagram. This diagram is created using a flowchart generation library (e.g., Graphviz) and visually represents the business process. The generated requirements definition diagram is displayed on the user's terminal via a web interface.

[0832] Next, the user reviews the requirements definition diagram and selects the specific parts they want to automate. A detailed analysis of the selected parts is then performed, and the results are visualized in detail using a visualization tool (e.g., D3.js). This allows the user to understand the details of the business processes of the selected parts.

[0833] The server also compares the operational manual with the systemized process and calculates the time-saving effect. Using statistical algorithms, it calculates how much work time will be reduced by systemization and presents the results to the user.

[0834] Furthermore, the server provides optimal systemization solutions and specific programming methods based on the analysis results and user requirements. This includes the use of specific software frameworks and APIs.

[0835] Employees at the logistics center wear smart glasses (e.g., Google Glass, Vuzix) and perform their tasks while checking the work procedures displayed on the glasses. The smart glasses accept the next instruction using voice recognition, which allows them to display appropriate work instructions in real time.

[0836] Specific example

[0837] For example, when employees perform product inspection work at a logistics center, they wear smart glasses. The glasses display instructions such as "Please scan the product," and when they say "next" via voice prompt, the next step, "Please check the condition of the product," is displayed. This allows employees to work efficiently while confirming the steps.

[0838] Example of a prompt

[0839] "Upload the operational manual and use OCR and natural language processing to extract the operational procedures. Display the extracted procedures on smart glasses and use voice recognition to detect the next instruction and proceed to the next step."

[0840] In this way, this invention automates everything from the analysis of operational manuals to the systemization process, resulting in a significant improvement in operational efficiency at logistics centers.

[0841] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0842] Step 1:

[0843] The user uploads a work manual file from their terminal to the server. When the user selects the work manual file from their terminal and presses the "Upload" button, the file is transferred to the server. In this process, the input is the work manual file, and the output is the file being saved on the server.

[0844] Step 2:

[0845] The server analyzes the content of the uploaded business manuals and extracts business processes and elements. First, the server uses OCR technology to convert the business manuals into text data. Next, it uses a natural language processing module (e.g., SpaCy, NLTK) to identify business procedures, roles, triggers, and conditions. In this process, the input is text data, and the output is the extracted business processes and elements. Specifically, the OCR module analyzes image data, and the natural language processing module analyzes text to identify specific elements.

[0846] Step 3:

[0847] Based on the extracted information, the server generates a requirements definition diagram. This is done using a flowchart generation library (e.g., Graphviz). The input is the extracted business processes and elements, and the output is a visual requirements definition diagram. The server converts the flow of business processes into a diagram using the library and presents it in a user-friendly format.

[0848] Step 4:

[0849] The user selects the parts they want to automate from the requirements diagram. The server displays the requirements diagram via a web interface, allowing the user to select the parts they want to automate using mouse clicks or taps. The input is the entire requirements diagram, and the output is the data for the parts selected by the user. The server accepts user input and understands the selected parts.

[0850] Step 5:

[0851] The server analyzes the detailed requirements of the selected portion and displays them using a visualization tool (e.g., D3.js). It analyzes the selected data in detail and displays the results graphically. The input is the data of the selected business portion, and the output is a visualization of the detailed analysis results. Specifically, it analyzes the selected data in detail and depicts the analysis results as a diagram.

[0852] Step 6:

[0853] The server compares the contents of the operational manual with the systemized process and calculates the time reduction effect. A statistical algorithm is used for this calculation. Inputs include analysis results and data on the systemized process, while output is a specific numerical value regarding the time reduction effect. The comparison algorithm is used to process the data and calculate the time reduction effect.

[0854] Step 7:

[0855] The server provides systemization solutions and specific programming methods. This includes the use of specific software frameworks and APIs. Inputs are analysis results and user requirements, while outputs are recommended solutions and specific programming methods. Based on the analysis data, the server selects the optimal solution and generates specific program examples.

[0856] Step 8:

[0857] The smart glasses display work procedures and provide voice commands to guide the user to the next step. The smart glasses' display shows the work procedures, and voice recognition (e.g., Google Speech-to-Text) is used to accept the next instruction. Input consists of work procedures and voice commands, while output is a display of the next step. Specifically, the smart glasses display the next step based on the voice command they detect.

[0858] 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.

[0859] This invention relates to a system that automates and streamlines the process from analyzing business manuals to systematizing them. This system incorporates an emotion engine that recognizes user emotions and has the function to adjust the interface and provide support according to the user's emotional state. The program processing of this system is described below in natural language.

[0860] Uploading and analyzing business manuals

[0861] The user uploads the work manual file from their terminal to the server. The user uses the terminal's web interface to select the work manual file and clicks the upload button. The terminal then sends the selected file to the server.

[0862] The server receives the uploaded business manual content and begins analysis. The server converts the file content into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This allows for the extraction of business processes and elements.

[0863] Generation of Requirements Definition Diagrams

[0864] The server automatically generates a requirements definition diagram based on the extracted business processes and elements. The requirements definition diagram visually represents the flow of business processes and is provided in a format that is easy for the user to understand. The server uses a flowchart generation library to create a visual requirements definition diagram and displays it to the user through a web interface.

[0865] Selection and analysis of the systematization components

[0866] Users can select the parts they want to automate from the generated requirements definition diagram. The selected data is sent from the terminal to the server, which then performs a detailed analysis of those parts. The analysis results are displayed to the user using a detailed visualization tool. This allows the user to understand the details of the specific business processes to be automated.

[0867] Calculation of time-saving effect

[0868] The server compares the contents of the operational manual with the systematized process and calculates the time savings. This calculation uses a statistical algorithm to specifically show how much work time is saved through systemization. The calculation results are visualized and presented to the user.

[0869] Providing system solutions and programming methods.

[0870] Based on the analysis results and user requirements, the server proposes the optimal systemization solution. This may include specific software frameworks and API combinations. Furthermore, the server automatically generates specific programming methods and provides them to the user. The provided programming methods include sample code and programming procedures, allowing the user to proceed with implementation based on these.

[0871] Utilizing the Emotion Engine

[0872] During user interaction, the emotion engine recognizes the user's emotional state. This emotion engine analyzes the user's emotions through voice and text analysis. Based on the analysis results, the server adjusts the interface according to the user's emotional state. For example, if the user is feeling confused or frustrated, the system will adjust to provide more detailed explanations and guidance. Support messages and guidance will also be provided according to the user's emotional state.

[0873] Specific example: Systematization of product inventory management

[0874] For example, if a user uploads a business manual for "product inventory management," the system will operate as follows:

[0875] 1. The user uploads the product inventory management manual file from their terminal to the server.

[0876] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[0877] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[0878] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[0879] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[0880] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[0881] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[0882] 8. The emotion engine analyzes the user's emotions from their voice and text, and if the user is confused, the system adjusts the interface to provide more detailed explanations or additional guidance.

[0883] This allows users to smoothly define requirements based on operational manuals and achieve efficient system implementation. The use of an emotion engine improves the user experience, leading to further efficiency improvements and increased user satisfaction.

[0884] The following describes the processing flow.

[0885] Step 1:

[0886] The user uploads the work manual file from their terminal to the server. The user selects the work manual file through the terminal's web interface and clicks the upload button. The terminal then sends the selected file to the server.

[0887] Step 2:

[0888] The server receives the uploaded business manual and begins analysis. The server converts the file contents into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This extracts the business processes and elements.

[0889] Step 3:

[0890] The server generates a requirements definition diagram based on the extracted information. The server uses a flowchart generation library to automatically generate flowcharts of business processes. The generated requirements definition diagram is displayed to the user through a web interface in a visually easy-to-understand format.

[0891] Step 4:

[0892] The user selects the parts they want to automate from the generated requirements diagram. The user reviews the requirements diagram and clicks to select the parts they wish to automate. The terminal sends the data for the selected parts to the server.

[0893] Step 5:

[0894] The server performs a detailed analysis of the selected portion. Based on the received data, the server performs a detailed analysis of the selected business process. The server uses detailed visualization tools to generate the analysis results as visual flowcharts and ER diagrams, which are then displayed to the user.

[0895] Step 6:

[0896] The server compares the contents of the operational manual with the process after systemization and calculates the time savings. The server uses a statistical algorithm to calculate the time saved by systemization. The calculation results are visualized and presented to the user.

[0897] Step 7:

[0898] The server provides the optimal systemization solution and specific programming methods. Based on the analysis results and user requirements, the server selects the optimal systemization solution (such as a combination of specific software frameworks and APIs). Furthermore, the server automatically generates sample code and programming instructions and provides them to the user.

[0899] Step 8:

[0900] The emotion engine recognizes the user's emotional state. The terminal and server collect the user's emotions through voice or text input, and the emotion engine analyzes this data. Based on the analysis results, the server adjusts the interface according to the user's emotional state. For example, if the user is confused, the server provides detailed explanations or additional guidance.

[0901] Specific example: Systematization of product inventory management

[0902] Step 1:

[0903] The user uploads the "Product Inventory Management" business manual file to the server using a terminal.

[0904] Step 2:

[0905] The server receives the uploaded manual, converts it into text data, applies a natural language processing module, and extracts business processes such as "order placement," "procurement," and "inventory update."

[0906] Step 3:

[0907] The server generates a requirements definition diagram based on the extracted information and displays this diagram, including the "flow from order placement to inventory update," to the user.

[0908] Step 4:

[0909] The user reviews the requirements diagram and selects to automate the "inventory update process." The terminal then sends the selected data to the server.

[0910] Step 5:

[0911] The server analyzes the details of the "inventory update process," generates a detailed flowchart, and displays it to the user.

[0912] Step 6:

[0913] The server calculates the time saved by systematizing the inventory update process and presents to the user that a 50% time reduction is possible compared to the traditional manual process.

[0914] Step 7:

[0915] The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, including specific API call code.

[0916] Step 8:

[0917] The emotion engine analyzes the user's emotions from their voice and text, and if the user appears confused, the server adjusts the interface to provide more detailed explanations and additional guidance.

[0918] (Example 2)

[0919] 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."

[0920] Automating the entire process, from analyzing existing business manuals and generating requirements definition diagrams to implementing systems and improving operational efficiency, is challenging. Furthermore, to enhance the user experience, it's necessary to accurately recognize the user's emotional state during operation and for the system to respond appropriately accordingly. A system is needed that can efficiently and appropriately address these challenges.

[0921] 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.

[0922] In this invention, the server includes means for uploading electronic files of business manuals, means for analyzing the contents of the uploaded business manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting parts to be systematized from the generated requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a detailed visualization tool, means for comparing the business manual with the systematized process and calculating the time reduction effect using statistical methods, means for providing a systematization solution and specific programming methods, and means including an emotion engine that adjusts the interface based on the user's emotional state. As a result, the process from business manual analysis to systematization is automated, enabling improved user experience and a significant increase in business efficiency.

[0923] A "business manual" is a document that outlines work procedures, roles, rules, and other information within a company or organization.

[0924] An "electronic file" is a digital document or data file that can be handled by a computer.

[0925] "Uploading" refers to the act of transferring data or files from a user's device to a server or cloud storage.

[0926] A "natural language processing module" is software or an algorithm that analyzes natural language data, such as text and speech, to extract and understand its meaning.

[0927] A "business process" is a set of steps and activities necessary to complete a specific task.

[0928] A "requirements definition diagram" is a diagram that visually represents business processes and elements, and serves as the foundation for system development.

[0929] A "visualization tool" is software used to visually display and analyze data and information.

[0930] A "statistical algorithm" refers to statistical methods and calculation procedures used for data analysis and prediction.

[0931] A "systemization solution" refers to specific technical measures or proposals aimed at automating and streamlining business processes.

[0932] "Programming method" refers to the way a program is written or the procedures involved in achieving a specific task or solution.

[0933] An "emotion engine" is software or a system that analyzes a user's emotional state in real time and provides appropriate feedback and interface adjustments.

[0934] This invention relates to a system that automates and streamlines the process from analyzing business manuals to systematizing them. This system incorporates an emotion engine that recognizes the user's emotional state and has functions to adjust the interface and provide support.

[0935] Uploading and analyzing business manuals

[0936] The user uploads an electronic file of the work manual from their terminal to the server. The user uses the terminal's web interface to select the work manual file and clicks the upload button. The terminal sends the selected file to the server via an HTTP POST request. The server parses the received file and converts it into text data. This parsing is performed using a natural language processing module (e.g., spaCy or NLTK) to identify elements such as work procedures, roles, triggers, and conditions.

[0937] Generation of Requirements Definition Diagrams

[0938] The server generates a requirements definition diagram using a flowchart drawing library (e.g., Graphviz) based on the extracted business processes and elements. The requirements definition diagram is displayed to the user via a web interface, allowing the user to visually understand the business processes.

[0939] Selection and analysis of the systematization components

[0940] The user selects the part of the requirements diagram they want to automate via a web interface. For example, the user selects the "Inventory Update" process by clicking on it. The selected data is sent from the terminal to the server, which then performs a detailed analysis of that part. The analysis results are displayed to the user using a detailed visualization tool (e.g., D3.js).

[0941] Calculation of time-saving effect

[0942] The server compares the contents of the operational manual with the systematized process and calculates the time savings. This calculation uses a statistical algorithm (e.g., Scikit-learn in Python) to specifically demonstrate the time savings achieved through systematization. The calculation results are visualized and presented to the user.

[0943] Providing system solutions and programming methods.

[0944] Based on the analysis results and user requirements, the server proposes an appropriate systemization solution. For example, it might suggest "using the inventory module of an ERP system." This proposal would also include appropriate frameworks and APIs (e.g., Django or Flask). The server provides specific programming methods and offers sample code and programming instructions to help the user implement the solution.

[0945] Utilizing the Emotion Engine

[0946] While the user is interacting with the system, an emotion engine recognizes the user's emotional state. This emotion engine analyzes the user's emotions through speech analysis (e.g., Google Speech-to-Text API) and text analysis (e.g., OpenAI's GPT). Based on the analysis results, the server adjusts the interface according to the user's emotional state. For example, if the user is feeling confused or frustrated, the system will adjust to provide detailed explanations and guidance.

[0947] Specific example: Systematization of product inventory management

[0948] For example, if a user uploads a business manual for "product inventory management," the system will operate as follows:

[0949] 1. The user uploads the product inventory management manual file from their terminal to the server.

[0950] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[0951] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[0952] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[0953] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[0954] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[0955] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[0956] 8. The emotion engine analyzes the user's emotions from their voice and text, and if the user is confused, the system adjusts the interface to provide more detailed explanations or additional guidance.

[0957] Example of a prompt

[0958] "Please upload the product inventory management operations manual, generate a requirements definition diagram, and systematize the inventory update process."

[0959] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0960] Step 1: Select and upload the business manual file.

[0961] The user uploads an electronic file of the work manual from their terminal to the server. The user uses the terminal's web interface to click the "Select File" button and chooses the work manual file. This action sends the selected file to the server when the user clicks the upload button. The server receives the HTTP POST request and stores the work manual file. Here, the input is the electronic file of the work manual selected by the user, and the output is the file stored on the server.

[0962] Step 2: Analyze the contents of the operational manual

[0963] The server analyzes the received business manual file. First, the server converts the file into text data, and then uses a natural language processing module (e.g., spaCy or NLTK) to identify elements such as business procedures, roles, triggers, and conditions. The input here is the text data of the business manual stored on the server, and the output is the extracted elements such as business procedures and roles. Specifically, the process involves analyzing the text content, extracting keywords and phrases, and converting it into structured data.

[0964] Step 3: Generating the Requirements Definition Diagram

[0965] The server generates a requirements definition diagram using a flowchart drawing library (e.g., Graphviz) based on the extracted business processes and elements. The generated requirements definition diagram is displayed to the user via a web interface. The input here is the extracted business processes and elements, and the output is the requirements definition diagram. Specifically, the operation involves converting the extracted data into a visual flowchart and displaying it in a user-friendly format.

[0966] Step 4: Selecting the parts to be systematized

[0967] The user selects the part of the requirements diagram they want to automate via a web interface. For example, clicking on the "Inventory Update" process selects that part. The selected data is sent from the terminal to the server. The input here is the part of the requirements diagram selected by the user, and the output is the selected data sent to the server. Specifically, the operation involves clicking on a particular part of the interface to select the part to be automated.

[0968] Step 5: Detailed Analysis and Visualization

[0969] The server performs a detailed analysis of the selected portion and displays it to the user using a detailed visualization tool (e.g., D3.js). The input here is a portion of the requirements diagram selected by the user, and the output is the detailed analysis results and their visualization data. Specific operations include data analysis of the selected portion, generation of a detailed flowchart, and display on the interface.

[0970] Step 6: Calculating the time-saving effect

[0971] The server compares the contents of the work manual with the systematized process and calculates the time savings. This calculation uses a statistical algorithm (e.g., Scikit-learn in Python). The input is the analysis results of the work manual and the data of the systematized process, and the output is the calculated time savings. The specific operation includes comparing the time required for manual and systematized tasks, calculating the effect using statistical methods, and visualizing the results.

[0972] Step 7: Provide systemization solutions and programming methods.

[0973] The server proposes the optimal systemization solution based on the analysis results and user requirements. For example, it might suggest "using the inventory module of the ERP system." It also provides specific programming methods (code examples and programming procedures). The input here is the analysis results and user requirements, while the output is the proposed solution and programming method. Specific operations include evaluating the analysis results, selecting an appropriate solution, and providing specific programming procedures.

[0974] Step 8: Utilizing the Emotional Engine

[0975] While the user is interacting with the system, the emotion engine recognizes the user's emotional state and adjusts the interface accordingly. This emotion engine uses speech analysis (e.g., Google Speech-to-Text API) and text analysis (e.g., OpenAI's GPT). The input is the user's voice or text data, and the output is the emotion analysis results and the adjusted interface. Specific operations include real-time analysis of the user's voice and text, identification of emotional state, and dynamic adjustment of the interface.

[0976] (Application Example 2)

[0977] 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."

[0978] Traditional systemization processes based on operational manuals require manual analysis and requirements definition, which are extremely time-consuming and labor-intensive. This results in decreased productivity and makes it difficult to improve operational efficiency. Furthermore, the inability to adjust the interface and provide support based on user emotions makes it difficult to improve the user experience.

[0979] 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.

[0980] In this invention, the server includes means for uploading business manual files, means for analyzing the contents of the uploaded business manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting parts to be systematized from the requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a visualization tool, means for comparing the business manual with the systematized process and calculating the time reduction effect, means for providing a systematization solution and specific programming methods, and means for adjusting the interface and support according to the user's emotional state using an emotion engine that recognizes the user's emotions. As a result, the analysis and systematization of business manuals are automated, significantly reducing labor and time, while enabling flexible support that responds to the user's emotions.

[0981] A "business manual" is a document that contains detailed explanations of specific business procedures, roles, triggers, and conditions.

[0982] "Method of uploading" refers to the function or interface that allows users to send work manual files from their terminal to the server.

[0983] The "means of analysis" refer to a function that converts the content of uploaded business manuals into text data and extracts business processes and elements using natural language processing technology.

[0984] A "requirements definition diagram" is a diagram that visually represents the flow and process of business operations, making it easy for users to understand.

[0985] "Systematizing" refers to automating business processes that were previously performed manually and improving efficiency through the use of software and systems.

[0986] A "visualization tool" is a tool or interface used to visually display analyzed data or process flows.

[0987] "Time-saving effect" refers to the amount of time saved by systematizing tasks compared to traditional manual processes.

[0988] A "systemization solution" refers to a combination of software frameworks and APIs optimized for automating specific business processes.

[0989] "Programming method" refers to the implementation method of a program, including specific procedures and sample code for systemization.

[0990] An "emotion engine" is a technology that recognizes a user's emotional state through voice and text analysis, and adjusts the interface and support based on the results.

[0991] An "interface" refers to the screen display and means of operation that a user uses to interact with a system.

[0992] "Support" refers to the guidance and supplementary information provided to users when using a system.

[0993] This invention aims to efficiently systematize operations based on the operation manuals for robots used in factories. In particular, it describes a system that provides information to the user visually using smart glasses and provides support tailored to the user's state using an emotion engine.

[0994] Uploading and analyzing business manuals

[0995] First, the user uploads the robot operation manual from their device to the server via smart glasses. Using the smart glasses' user interface, they select the manual file and send it to the cloud server. The server receives the uploaded manual and converts it into text data. The software used here includes a natural language processing (NLP) module, which extracts work procedures, roles, and other relevant information.

[0996] Generation of Requirements Definition Diagrams

[0997] The server automatically generates a requirements definition diagram based on the extracted business processes and elements. This process uses a flowchart generation library to visually represent the business flow. The generated requirements definition diagram is displayed on the smart glasses screen.

[0998] Selection and analysis of the systematization components

[0999] Users select the parts they want to systemize from a requirements definition diagram using smart glasses. The selected data is sent from the terminal to the server, which then performs a detailed analysis of that part. During this process, a detailed process flow is displayed using a visualization tool.

[1000] Calculation of time-saving effect

[1001] The server compares the contents of the operational manual with the systematized process and calculates the time-saving effect using a statistical algorithm. The calculation results are visualized and presented to the user.

[1002] Providing system solutions and programming methods.

[1003] Furthermore, the server proposes the optimal systemization solution based on the analysis results and user selections. This includes specific software frameworks, API usage methods, and sample code. This enables efficient implementation.

[1004] Utilizing the Emotion Engine

[1005] When a user uses smart glasses, the emotion engine recognizes the user's emotional state through voice and text analysis. For example, if the user is confused, the system provides a detailed explanation. The interface is also adjusted and support messages are provided according to the emotional state.

[1006] Specific example

[1007] For example, a new factory operator uploads a robot initial setup manual to smart glasses. The system extracts the robot operation procedures and generates an initial setup flowchart. The operator follows the flowchart displayed on the smart glasses, performing the operations step by step. If there are any questions, the glasses' emotion engine detects the operator's confusion and automatically displays detailed explanations or video tutorials. This allows even inexperienced operators to set up the robot with confidence.

[1008] Example of a prompt

[1009] Please describe the entire process of a system that automatically generates requirements definition diagrams from factory robot operation manuals and displays them to users using smart glasses, and provide a concrete example of how to use an emotion engine for user support.

[1010] This invention automates the analysis and systematization of business manuals, resulting in a significant reduction in labor and time, while also enabling flexible support tailored to the user's needs.

[1011] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1012] Step 1:

[1013] Uploading the business manual

[1014] The user selects a robot operation manual file using the user interface of the smart glasses and presses the upload button. This sends the selected manual file from the terminal (smart glasses) to the server.

[1015] Input: Business manual file

[1016] Output: Business manual file uploaded to the server

[1017] Step 2:

[1018] Analysis of business manuals

[1019] The server receives the uploaded business manual file and converts its contents into text data. A natural language processing (NLP) module is used to extract business processes and elements (procedures, roles, triggers, conditions, etc.).

[1020] Input: Uploaded business manual file

[1021] Output: Extracted business processes and elements

[1022] Step 3:

[1023] Generation of Requirements Definition Diagrams

[1024] The server uses a flowchart generation library to automatically generate requirements definition diagrams based on the extracted business processes and elements. The generated requirements definition diagrams are saved in the cloud and displayed on smart glasses.

[1025] Input: Extracted business processes and elements

[1026] Output: Requirements definition diagram

[1027] Step 4:

[1028] Selection of Systematization Components

[1029] The user selects the parts of the requirements diagram they want to automate through the display interface of their smart glasses. The selected data is then sent from the device to the server.

[1030] Input: Requirements definition diagram

[1031] Output: Selected systemization portion

[1032] Step 5:

[1033] Detailed analysis and visualization

[1034] The server analyzes the selected system components in detail and generates a detailed process flow. The generated flow is then displayed to the user in an easy-to-understand format using a visualization tool.

[1035] Input: Selected systemization portion

[1036] Output: Detailed process flow

[1037] Step 6:

[1038] Calculation of time-saving effect

[1039] The server compares the contents of the operational manual with the systematized process and uses a statistical algorithm to calculate the time savings. The calculation results are visualized and displayed on smart glasses.

[1040] Input: Detailed process flow

[1041] Output: Calculation results of time reduction effect

[1042] Step 7:

[1043] Providing system solutions and programming methods.

[1044] The server proposes the optimal systemization solution based on the analysis results and user requests. Furthermore, it provides specific program sample code and instructions on how to use the API.

[1045] Input: Calculation result of time reduction effect

[1046] Output: Systematized solution and specific program steps

[1047] Step 8:

[1048] Utilizing the Emotion Engine

[1049] When a user uses smart glasses, the emotion engine recognizes the user's emotional state through voice analysis and eye tracking. For example, if the user is confused, the system displays a detailed explanation or video tutorial.

[1050] Input: User sentiment data

[1051] Output: Interface adjustments and support information tailored to user sentiment.

[1052] 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.

[1053] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1054] 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.

[1055] [Fourth Embodiment]

[1056] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1057] 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.

[1058] 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).

[1059] 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.

[1060] 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.

[1061] 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).

[1062] 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.

[1063] 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.

[1064] 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.

[1065] 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.

[1066] 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.

[1067] 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.

[1068] 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".

[1069] This invention relates to a system that automates and streamlines the process from analyzing business manuals to systematizing them. The program processing of this system is described below in natural language.

[1070] Uploading and analyzing business manuals

[1071] The user uploads a business manual file from their terminal to the server. The server receives this file and begins analysis. Specifically, the server converts the file's contents into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This allows for the extraction of business processes and elements.

[1072] Generation of Requirements Definition Diagrams

[1073] The server automatically generates a requirements definition diagram based on the extracted business processes and elements. The requirements definition diagram visually represents the flow of business processes and is provided in a format that is easy for the user to understand. The server uses a flowchart generation library to create a visual requirements definition diagram and displays it to the user through a web interface.

[1074] Selection and analysis of the systematization components

[1075] Users can select the parts they want to automate from the generated requirements definition diagram. The selected data is sent from the terminal to the server, which then performs a detailed analysis of those parts. The analysis results are displayed to the user using a detailed visualization tool. This allows the user to understand the details of the specific business processes to be automated.

[1076] Calculation of time-saving effect

[1077] The server compares the contents of the operational manual with the systematized process and calculates the time savings. This calculation uses a statistical algorithm to specifically show how much work time is saved through systemization. The calculation results are visualized and presented to the user.

[1078] Providing system solutions and programming methods.

[1079] Based on the analysis results and user requirements, the server proposes the optimal systemization solution. This may include specific software frameworks and API combinations. Furthermore, the server automatically generates specific programming methods and provides them to the user. The provided programming methods include sample code and programming procedures, allowing the user to proceed with implementation based on these.

[1080] Specific example: Systematization of product inventory management

[1081] For example, if a user uploads a business manual for "product inventory management," the system will operate as follows:

[1082] 1. The user uploads the product inventory management manual file from their terminal to the server.

[1083] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[1084] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[1085] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[1086] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[1087] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[1088] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[1089] This allows users to smoothly define requirements based on business manuals and achieve efficient system implementation.

[1090] The following describes the processing flow.

[1091] Step 1:

[1092] The user uploads the work manual file from their terminal to the server. The user uses the terminal's web interface to select the work manual file and clicks the upload button. The terminal then sends the selected file to the server.

[1093] Step 2:

[1094] The server receives the uploaded business manual and begins analysis. The server converts the file contents into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This allows for the extraction of business processes and elements.

[1095] Step 3:

[1096] The server generates a requirements definition diagram based on the extracted information. The server analyzes the business process flow and uses a flowchart generation library to create a visual requirements definition diagram. The server displays the generated requirements definition diagram to the user through a web interface.

[1097] Step 4:

[1098] The user selects the parts they want to automate from the requirements diagram. The user reviews the displayed requirements diagram and clicks to select the parts they want to automate. The terminal sends the selected data to the server.

[1099] Step 5:

[1100] The server performs a detailed analysis of the selected portion. Based on the received data, the server performs a detailed analysis of the selected business process and generates detailed visualizations (flowcharts and ER diagrams). The server displays the generated diagrams to the user via a web interface.

[1101] Step 6:

[1102] The server compares the contents of the operational manual with the process after systemization and calculates the time savings. The server uses statistical algorithms to calculate the time saved by systemization. The calculation results are visualized and presented to the user.

[1103] Step 7:

[1104] The server provides the optimal systemization solution and specific programming methods. Based on the analysis results and user requirements, the server selects the appropriate systemization solution and automatically generates sample code and programming procedures. The server then presents this to the user through a web interface.

[1105] The above describes the detailed flow of program processing in the "RequirementsCraft" system and the specific actions performed at each processing step.

[1106] (Example 1)

[1107] 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".

[1108] The requirements definition and system development associated with the systemization of traditional business processes were often manual, time-consuming, and labor-intensive. Furthermore, there were concerns about errors and decreased efficiency in the process of extracting systemization requirements from business manuals. Additionally, the effectiveness of systemization was difficult to evaluate concretely beforehand, making the post-implementation effects uncertain. This led to delays in systemization aimed at improving business efficiency.

[1109] 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.

[1110] In this invention, the server includes means for uploading business procedure manual files, means for analyzing the contents of the uploaded business procedure manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting the parts to be systematized from the requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a visualization tool, means for comparing the business procedure manuals with the systematized processes and calculating the time reduction effect, and means for providing systematization solutions and specific programming methods. This makes it possible to automatically extract systematization requirements from business manuals and efficiently build systems. Furthermore, by evaluating the effects of systematization in advance, concrete effects can be expected before implementation.

[1111] A "work procedure manual" is a document that describes work processes and procedures, clearly outlining how to perform the work, the roles involved, and the conditions.

[1112] "Uploading" refers to the action of sending a file from a device to a server, and means transmitting digital data over the internet.

[1113] "Analysis" refers to the process of analyzing the content of data or documents to extract specific information or patterns.

[1114] A "business process" refers to a series of business procedures or activities performed to achieve a specific objective.

[1115] An "element" is a specific item or part that makes up a business process, and includes procedures, roles, triggers, conditions, etc.

[1116] A "requirements definition diagram" is a diagram that visually represents the interrelationships between business processes and elements, showing the flow and relationships of business procedures.

[1117] "Systematization" refers to the introduction of computer systems to automate business processes that are currently performed manually.

[1118] "Selection" refers to the act of choosing a specific item from among multiple options.

[1119] "Detailed requirements" refers to the specific conditions and specifications necessary for system implementation.

[1120] A "visualization tool" is a software tool used to visually display data and information, and includes tools that generate graphs, charts, and flowcharts.

[1121] "Time-saving effect" refers to the effect of streamlining business processes through systemization, thereby reducing the time required.

[1122] A "statistical algorithm" refers to a mathematical method used to analyze data and derive statistical conclusions or predictions.

[1123] A "systemization solution" refers to the optimal methods and technical proposals for systematizing specific business processes.

[1124] "Programming methods" refer to the specific coding procedures and techniques used to build computer systems.

[1125] This invention is a system that automatically automates the analysis of work procedure manuals to improve efficiency. Specifically, it consists of the following means.

[1126] First, the user uploads the work procedure manual file from their terminal to the server. This upload is done via an HTML form or a file upload API. The user selects the work procedure manual file (e.g., PDF, Word, etc.) and submits it by clicking the "Upload" button.

[1127] Next, the server analyzes the contents of the uploaded business procedure manual. This analysis uses Apache Tika to convert the file into text data and then uses Python's natural language processing module (e.g., NLTK, spaCy) to identify elements such as business procedures, roles, triggers, and conditions. In this process, business processes and elements are identified and extracted.

[1128] Next, the server generates a requirements definition diagram based on the extracted information. A flowchart generation library (e.g., Graphviz, PlantUML) is used to create a visual requirements definition diagram. This requirements definition diagram is in a user-friendly format, and the server displays this diagram to the user through a web interface.

[1129] From the displayed requirements diagram, the user selects the parts they want to automate. This selection is made by clicking on the requirements diagram, and the selection data is sent from the terminal to the server. The server performs a detailed analysis of the selected parts and uses a natural language processing module again to identify specific procedures and necessary resources. The analysis results are generated as detailed flowcharts and data flow diagrams and provided to the user.

[1130] Furthermore, the server compares the manual work procedures with the systemized processes and calculates the time savings using statistical algorithms. This calculation uses tools such as Python's pandas and scikit-learn, and the results are visualized and presented to the user as graphs and charts. For example, it might show a specific effect such as, "Systematizing the inventory update process can reduce time by 50%."

[1131] Finally, the server proposes the optimal systemization solution based on the analysis results and user requirements. This may include specific software frameworks (e.g., Django, Flask) and API combinations. The server also automatically generates specific programming methods and provides the user with sample code and programming instructions, allowing the user to proceed with implementation.

[1132] Specific example: Systematization of product inventory management

[1133] For example, if a user uploads a business procedure manual for "product inventory management," the system will operate as follows:

[1134] 1. The user uploads a product inventory management procedure file from their terminal to the server.

[1135] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[1136] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[1137] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[1138] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[1139] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[1140] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[1141] Examples of prompts to input into a generative AI model

[1142] When inputting a specific example of what happens when a user uploads a "Product Inventory Management Procedure Manual" into the AI ​​model, use the following prompt message:

[1143] The user uploaded a business procedure manual for product inventory management from their terminal to the server. The server analyzed the manual, extracted business processes such as "order taking," "procurement," and "inventory updating," and displayed an automatically generated requirements definition diagram to the user. The user chose to automate the "inventory updating process," and the server generated a detailed flowchart and provided it to the user. It was calculated that this would reduce the time required by 50% compared to the traditional manual process, and this result was presented to the user. Finally, the server proposed a solution using the "inventory module of the ERP system" and provided the user with program examples, including specific API call codes.

[1144] According to the embodiment for carrying out this invention, the process from uploading work procedure manuals to systemization and calculation of time-saving effects is efficiently executed.

[1145] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1146] Step 1: Upload the operational procedures manual.

[1147] The user uploads the work procedure manual file from their terminal to the server. The user selects the file using the browser's file upload function and clicks the "Upload" button. The input file can be in formats such as PDF or Word, and the output is a file saved on the server. This process imports the work procedure manual to the server.

[1148] Step 2: Analysis of operational procedures

[1149] The server analyzes the uploaded business procedure manuals. First, the server uses the Apache Tika library to convert the files into text data. The converted text is then analyzed using a natural language processing module (e.g., NLTK or spaCy) to identify elements such as business procedures, roles, triggers, and conditions. The input is text data, and the output is the result of extracting business processes and elements. Specifically, business processes such as "order taking," "inventory check," and "shipping preparation" are identified.

[1150] Step 3: Generating the Requirements Definition Diagram

[1151] The server generates a requirements definition diagram based on the extracted business processes and elements. The server creates a visual flowchart using a flowchart generation library (e.g., Graphviz or PlantUML). This flowchart shows the flow of the business process and is displayed in an easy-to-understand format for the user. The input is the extracted business process results, and the output is the generated requirements definition diagram. The requirements definition diagram is displayed to the user via a browser.

[1152] Step 4: Selecting the parts to be systematized

[1153] The user selects the parts they want to automate from the generated requirements diagram. The user makes this selection by clicking on the business processes they want to automate within the requirements diagram. The input is the requirements diagram, and the output is the data for the selected parts to be automated. This data is sent from the terminal to the server.

[1154] Step 5: Detailed analysis of the systemized portion

[1155] The server performs a detailed analysis of the systemization portion selected by the user. Using a natural language processing module again, it identifies the corresponding specific steps and required resources for the selected portion. The input is the data of the selected systemization portion, and the output is a detailed flowchart or data flow diagram. The analysis results are displayed to the user using a visualization tool (e.g., D3.js).

[1156] Step 6: Calculating the time-saving effect

[1157] The server compares the contents of the work procedure manual with the systematized process and calculates the time reduction effect using a statistical algorithm. The server analyzes the data using Python's pandas and scikit-learn to calculate how much work time is reduced by the systematization. The input is the analysis results of the work procedure manual and the process data after systematization, and the output is a report on the time reduction effect. The calculation results are presented to the user as a graph.

[1158] Step 7: Provide systemization solutions and programming methods.

[1159] The server proposes the optimal systemization solution based on the analysis results and user requirements. The server suggests specific software frameworks (e.g., Django, Flask) and API combinations, and automatically generates concrete programming instructions. The input is the analysis results and user selections, and the output is the proposed systemization solution and program examples. The generated program examples and procedures are provided to the user via a web interface.

[1160] (Application Example 1)

[1161] 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".

[1162] Traditional process for systematizing operational manuals required significant time and effort, from manual analysis and requirements definition to system selection and provision of programming methods. Furthermore, in environments demanding high efficiency, such as logistics centers, efficient work instructions and real-time procedure verification based on operational manuals were difficult, often leading to delays and errors. In particular, product inspection and inventory management required employees to memorize numerous procedures, which reduced work efficiency. There is a need to solve these problems and improve operational efficiency and accuracy.

[1163] 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.

[1164] In this invention, the server includes means for uploading business manual files, means for analyzing the contents of the uploaded business manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting parts to be systematized from the requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a visualization tool, means for comparing the business manual with the systematized process and calculating the time reduction effect, means for providing a systematization solution and a specific program, and means for displaying business procedures on smart glasses and instructing the next step via voice control. This automates and streamlines the systematization process of business manuals, enabling real-time display of appropriate procedures and voice-controlled next instructions, particularly in product inspection and inventory work at logistics centers.

[1165] "A means of uploading business manual files" refers to a mechanism for users to transfer document files containing procedures and rules related to their work to a server.

[1166] "A means of analyzing the contents of uploaded business manuals and extracting business processes and elements" refers to a system in which the server reads the contents of the received business manuals as digital data and uses natural language processing technology to identify elements such as business procedures and roles.

[1167] "A means of generating requirements definition diagrams based on extracted information" refers to a mechanism for creating visual flowcharts based on analyzed business flows and elements.

[1168] "A means of selecting the parts to be systematized from the requirements definition diagram" refers to a mechanism that allows users to review the generated requirements definition diagram and select the specific business processes they want to systematize.

[1169] "A means of analyzing the detailed requirements of the selected portion and displaying them with a visualization tool" refers to a system that further analyzes the business portion selected by the user and graphically displays the analysis results to the user.

[1170] "A method for comparing business manuals with systemized processes and calculating time savings" refers to a mechanism that compares traditional business procedures with systemized procedures and uses statistical algorithms to calculate how much time is saved after systemization.

[1171] "Means of providing systemized solutions and specific programs" refers to a mechanism that provides users with solutions utilizing specific software frameworks and APIs, as well as specific methods for their implementation, in order to improve the efficiency of business operations.

[1172] "A means of displaying work procedures on smart glasses and instructing the next step via voice control" refers to a system that uses the display of smart glasses to show work procedures and utilizes voice recognition functionality to instruct the next step in response to the worker's commands.

[1173] This invention is a system for improving the efficiency of product inspection and inventory management in logistics centers. The system's program processing and the hardware and software used are described in detail below.

[1174] The server first accepts user uploads of business manual files. To analyze the contents of the business manual, OCR (Optical Character Recognition) technology is used to convert it into text data, and then a natural language processing module (e.g., SpaCy, NLTK) is used. This allows elements such as business procedures, roles, triggers, and conditions to be extracted.

[1175] Based on the extracted information, the server generates a requirements definition diagram. This diagram is created using a flowchart generation library (e.g., Graphviz) and visually represents the business process. The generated requirements definition diagram is displayed on the user's terminal via a web interface.

[1176] Next, the user reviews the requirements definition diagram and selects the specific parts they want to automate. A detailed analysis of the selected parts is then performed, and the results are visualized in detail using a visualization tool (e.g., D3.js). This allows the user to understand the details of the business processes of the selected parts.

[1177] The server also compares the operational manual with the systemized process and calculates the time-saving effect. Using statistical algorithms, it calculates how much work time will be reduced by systemization and presents the results to the user.

[1178] Furthermore, the server provides optimal systemization solutions and specific programming methods based on the analysis results and user requirements. This includes the use of specific software frameworks and APIs.

[1179] Employees at the logistics center wear smart glasses (e.g., Google Glass, Vuzix) and perform their tasks while checking the work procedures displayed on the glasses. The smart glasses accept the next instruction using voice recognition, which allows them to display appropriate work instructions in real time.

[1180] Specific example

[1181] For example, when employees perform product inspection work at a logistics center, they wear smart glasses. The glasses display instructions such as "Please scan the product," and when they say "next" via voice prompt, the next step, "Please check the condition of the product," is displayed. This allows employees to work efficiently while confirming the steps.

[1182] Example of a prompt

[1183] "Upload the operational manual and use OCR and natural language processing to extract the operational procedures. Display the extracted procedures on smart glasses and use voice recognition to detect the next instruction and proceed to the next step."

[1184] In this way, this invention automates everything from the analysis of operational manuals to the systemization process, resulting in a significant improvement in operational efficiency at logistics centers.

[1185] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1186] Step 1:

[1187] The user uploads a work manual file from their terminal to the server. When the user selects the work manual file from their terminal and presses the "Upload" button, the file is transferred to the server. In this process, the input is the work manual file, and the output is the file being saved on the server.

[1188] Step 2:

[1189] The server analyzes the content of the uploaded business manuals and extracts business processes and elements. First, the server uses OCR technology to convert the business manuals into text data. Next, it uses a natural language processing module (e.g., SpaCy, NLTK) to identify business procedures, roles, triggers, and conditions. In this process, the input is text data, and the output is the extracted business processes and elements. Specifically, the OCR module analyzes image data, and the natural language processing module analyzes text to identify specific elements.

[1190] Step 3:

[1191] Based on the extracted information, the server generates a requirements definition diagram. This is done using a flowchart generation library (e.g., Graphviz). The input is the extracted business processes and elements, and the output is a visual requirements definition diagram. The server converts the flow of business processes into a diagram using the library and presents it in a user-friendly format.

[1192] Step 4:

[1193] The user selects the parts they want to automate from the requirements diagram. The server displays the requirements diagram via a web interface, allowing the user to select the parts they want to automate using mouse clicks or taps. The input is the entire requirements diagram, and the output is the data for the parts selected by the user. The server accepts user input and understands the selected parts.

[1194] Step 5:

[1195] The server analyzes the detailed requirements of the selected portion and displays them using a visualization tool (e.g., D3.js). It analyzes the selected data in detail and displays the results graphically. The input is the data of the selected business portion, and the output is a visualization of the detailed analysis results. Specifically, it analyzes the selected data in detail and depicts the analysis results as a diagram.

[1196] Step 6:

[1197] The server compares the contents of the operational manual with the systemized process and calculates the time reduction effect. A statistical algorithm is used for this calculation. Inputs include analysis results and data on the systemized process, while output is a specific numerical value regarding the time reduction effect. The comparison algorithm is used to process the data and calculate the time reduction effect.

[1198] Step 7:

[1199] The server provides systemization solutions and specific programming methods. This includes the use of specific software frameworks and APIs. Inputs are analysis results and user requirements, while outputs are recommended solutions and specific programming methods. Based on the analysis data, the server selects the optimal solution and generates specific program examples.

[1200] Step 8:

[1201] The smart glasses display work procedures and provide voice commands to guide the user to the next step. The smart glasses' display shows the work procedures, and voice recognition (e.g., Google Speech-to-Text) is used to accept the next instruction. Input consists of work procedures and voice commands, while output is a display of the next step. Specifically, the smart glasses display the next step based on the voice command they detect.

[1202] 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.

[1203] This invention relates to a system that automates and streamlines the process from analyzing business manuals to systematizing them. This system incorporates an emotion engine that recognizes user emotions and has the function to adjust the interface and provide support according to the user's emotional state. The program processing of this system is described below in natural language.

[1204] Uploading and analyzing business manuals

[1205] The user uploads the work manual file from their terminal to the server. The user uses the terminal's web interface to select the work manual file and clicks the upload button. The terminal then sends the selected file to the server.

[1206] The server receives the uploaded business manual content and begins analysis. The server converts the file content into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This allows for the extraction of business processes and elements.

[1207] Generation of Requirements Definition Diagrams

[1208] The server automatically generates a requirements definition diagram based on the extracted business processes and elements. The requirements definition diagram visually represents the flow of business processes and is provided in a format that is easy for the user to understand. The server uses a flowchart generation library to create a visual requirements definition diagram and displays it to the user through a web interface.

[1209] Selection and analysis of the systematization components

[1210] Users can select the parts they want to automate from the generated requirements definition diagram. The selected data is sent from the terminal to the server, which then performs a detailed analysis of those parts. The analysis results are displayed to the user using a detailed visualization tool. This allows the user to understand the details of the specific business processes to be automated.

[1211] Calculation of time-saving effect

[1212] The server compares the contents of the operational manual with the systematized process and calculates the time savings. This calculation uses a statistical algorithm to specifically show how much work time is saved through systemization. The calculation results are visualized and presented to the user.

[1213] Providing system solutions and programming methods.

[1214] Based on the analysis results and user requirements, the server proposes the optimal systemization solution. This may include specific software frameworks and API combinations. Furthermore, the server automatically generates specific programming methods and provides them to the user. The provided programming methods include sample code and programming procedures, allowing the user to proceed with implementation based on these.

[1215] Utilizing the Emotion Engine

[1216] During user interaction, the emotion engine recognizes the user's emotional state. This emotion engine analyzes the user's emotions through voice and text analysis. Based on the analysis results, the server adjusts the interface according to the user's emotional state. For example, if the user is feeling confused or frustrated, the system will adjust to provide more detailed explanations and guidance. Support messages and guidance will also be provided according to the user's emotional state.

[1217] Specific example: Systematization of product inventory management

[1218] For example, if a user uploads a business manual for "product inventory management," the system will operate as follows:

[1219] 1. The user uploads the product inventory management manual file from their terminal to the server.

[1220] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[1221] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[1222] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[1223] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[1224] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[1225] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[1226] 8. The emotion engine analyzes the user's emotions from their voice and text, and if the user is confused, the system adjusts the interface to provide more detailed explanations or additional guidance.

[1227] This allows users to smoothly define requirements based on operational manuals and achieve efficient system implementation. The use of an emotion engine improves the user experience, leading to further efficiency improvements and increased user satisfaction.

[1228] The following describes the processing flow.

[1229] Step 1:

[1230] The user uploads the work manual file from their terminal to the server. The user selects the work manual file through the terminal's web interface and clicks the upload button. The terminal then sends the selected file to the server.

[1231] Step 2:

[1232] The server receives the uploaded business manual and begins analysis. The server converts the file contents into text data and uses a natural language processing module to identify elements such as business procedures, roles, triggers, and conditions. This extracts the business processes and elements.

[1233] Step 3:

[1234] The server generates a requirements definition diagram based on the extracted information. The server uses a flowchart generation library to automatically generate flowcharts of business processes. The generated requirements definition diagram is displayed to the user through a web interface in a visually easy-to-understand format.

[1235] Step 4:

[1236] The user selects the parts they want to automate from the generated requirements diagram. The user reviews the requirements diagram and clicks to select the parts they wish to automate. The terminal sends the data for the selected parts to the server.

[1237] Step 5:

[1238] The server performs a detailed analysis of the selected portion. Based on the received data, the server performs a detailed analysis of the selected business process. The server uses detailed visualization tools to generate the analysis results as visual flowcharts and ER diagrams, which are then displayed to the user.

[1239] Step 6:

[1240] The server compares the contents of the operational manual with the process after systemization and calculates the time savings. The server uses a statistical algorithm to calculate the time saved by systemization. The calculation results are visualized and presented to the user.

[1241] Step 7:

[1242] The server provides the optimal systemization solution and specific programming methods. Based on the analysis results and user requirements, the server selects the optimal systemization solution (such as a combination of specific software frameworks and APIs). Furthermore, the server automatically generates sample code and programming instructions and provides them to the user.

[1243] Step 8:

[1244] The emotion engine recognizes the user's emotional state. The terminal and server collect the user's emotions through voice or text input, and the emotion engine analyzes this data. Based on the analysis results, the server adjusts the interface according to the user's emotional state. For example, if the user is confused, the server provides detailed explanations or additional guidance.

[1245] Specific example: Systematization of product inventory management

[1246] Step 1:

[1247] The user uploads the "Product Inventory Management" business manual file to the server using a terminal.

[1248] Step 2:

[1249] The server receives the uploaded manual, converts it into text data, applies a natural language processing module, and extracts business processes such as "order placement," "procurement," and "inventory update."

[1250] Step 3:

[1251] The server generates a requirements definition diagram based on the extracted information and displays this diagram, including the "flow from order placement to inventory update," to the user.

[1252] Step 4:

[1253] The user reviews the requirements diagram and selects to automate the "inventory update process." The terminal then sends the selected data to the server.

[1254] Step 5:

[1255] The server analyzes the details of the "inventory update process," generates a detailed flowchart, and displays it to the user.

[1256] Step 6:

[1257] The server calculates the time saved by systematizing the inventory update process and presents to the user that a 50% time reduction is possible compared to the traditional manual process.

[1258] Step 7:

[1259] The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, including specific API call code.

[1260] Step 8:

[1261] The emotion engine analyzes the user's emotions from their voice and text, and if the user appears confused, the server adjusts the interface to provide more detailed explanations and additional guidance.

[1262] (Example 2)

[1263] 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".

[1264] Automating the entire process, from analyzing existing business manuals and generating requirements definition diagrams to implementing systems and improving operational efficiency, is challenging. Furthermore, to enhance the user experience, it's necessary to accurately recognize the user's emotional state during operation and for the system to respond appropriately accordingly. A system is needed that can efficiently and appropriately address these challenges.

[1265] 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.

[1266] In this invention, the server includes means for uploading electronic files of business manuals, means for analyzing the contents of the uploaded business manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting parts to be systematized from the generated requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a detailed visualization tool, means for comparing the business manual with the systematized process and calculating the time reduction effect using statistical methods, means for providing a systematization solution and specific programming methods, and means including an emotion engine that adjusts the interface based on the user's emotional state. As a result, the process from business manual analysis to systematization is automated, enabling improved user experience and a significant increase in business efficiency.

[1267] A "business manual" is a document that outlines work procedures, roles, rules, and other information within a company or organization.

[1268] An "electronic file" is a digital document or data file that can be handled by a computer.

[1269] "Uploading" refers to the act of transferring data or files from a user's device to a server or cloud storage.

[1270] A "natural language processing module" is software or an algorithm that analyzes natural language data, such as text and speech, to extract and understand its meaning.

[1271] A "business process" is a set of steps and activities necessary to complete a specific task.

[1272] A "requirements definition diagram" is a diagram that visually represents business processes and elements, and serves as the foundation for system development.

[1273] A "visualization tool" is software used to visually display and analyze data and information.

[1274] A "statistical algorithm" refers to statistical methods and calculation procedures used for data analysis and prediction.

[1275] A "systemization solution" refers to specific technical measures or proposals aimed at automating and streamlining business processes.

[1276] "Programming method" refers to the way a program is written or the procedures involved in achieving a specific task or solution.

[1277] An "emotion engine" is software or a system that analyzes a user's emotional state in real time and provides appropriate feedback and interface adjustments.

[1278] This invention relates to a system that automates and streamlines the process from analyzing business manuals to systematizing them. This system incorporates an emotion engine that recognizes the user's emotional state and has functions to adjust the interface and provide support.

[1279] Uploading and analyzing business manuals

[1280] The user uploads an electronic file of the work manual from their terminal to the server. The user uses the terminal's web interface to select the work manual file and clicks the upload button. The terminal sends the selected file to the server via an HTTP POST request. The server parses the received file and converts it into text data. This parsing is performed using a natural language processing module (e.g., spaCy or NLTK) to identify elements such as work procedures, roles, triggers, and conditions.

[1281] Generation of Requirements Definition Diagrams

[1282] The server generates a requirements definition diagram using a flowchart drawing library (e.g., Graphviz) based on the extracted business processes and elements. The requirements definition diagram is displayed to the user via a web interface, allowing the user to visually understand the business processes.

[1283] Selection and analysis of the systematization components

[1284] The user selects the part of the requirements diagram they want to automate via a web interface. For example, the user selects the "Inventory Update" process by clicking on it. The selected data is sent from the terminal to the server, which then performs a detailed analysis of that part. The analysis results are displayed to the user using a detailed visualization tool (e.g., D3.js).

[1285] Calculation of time-saving effect

[1286] The server compares the contents of the operational manual with the systematized process and calculates the time savings. This calculation uses a statistical algorithm (e.g., Scikit-learn in Python) to specifically demonstrate the time savings achieved through systematization. The calculation results are visualized and presented to the user.

[1287] Providing system solutions and programming methods.

[1288] Based on the analysis results and user requirements, the server proposes an appropriate systemization solution. For example, it might suggest "using the inventory module of an ERP system." This proposal would also include appropriate frameworks and APIs (e.g., Django or Flask). The server provides specific programming methods and offers sample code and programming instructions to help the user implement the solution.

[1289] Utilizing the Emotion Engine

[1290] While the user is interacting with the system, an emotion engine recognizes the user's emotional state. This emotion engine analyzes the user's emotions through speech analysis (e.g., Google Speech-to-Text API) and text analysis (e.g., OpenAI's GPT). Based on the analysis results, the server adjusts the interface according to the user's emotional state. For example, if the user is feeling confused or frustrated, the system will adjust to provide detailed explanations and guidance.

[1291] Specific example: Systematization of product inventory management

[1292] For example, if a user uploads a business manual for "product inventory management," the system will operate as follows:

[1293] 1. The user uploads the product inventory management manual file from their terminal to the server.

[1294] 2. The server analyzes the files and extracts business processes such as "order placement," "procurement," and "inventory update."

[1295] 3. Based on the extracted information, the server automatically generates a requirements definition diagram, including the "flow from order placement to inventory update," and displays it to the user.

[1296] 4. The user reviews the requirements definition diagram and chooses to systematize the "inventory update process".

[1297] 5. The server analyzes the details of the selected inventory update process, generates a detailed flowchart, and provides it to the user.

[1298] 6. The server calculates that systematizing the inventory update process can reduce the time required by 50% compared to traditional manual operations, and presents this result to the user.

[1299] 7. The server proposes a solution that "utilizes the inventory module of the ERP system" and provides the user with program examples, such as specific API call code.

[1300] 8. The emotion engine analyzes the user's emotions from their voice and text, and if the user is confused, the system adjusts the interface to provide more detailed explanations or additional guidance.

[1301] Example of a prompt

[1302] "Please upload the product inventory management operations manual, generate a requirements definition diagram, and systematize the inventory update process."

[1303] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1304] Step 1: Select and upload the business manual file.

[1305] The user uploads an electronic file of the work manual from their terminal to the server. The user uses the terminal's web interface to click the "Select File" button and chooses the work manual file. This action sends the selected file to the server when the user clicks the upload button. The server receives the HTTP POST request and stores the work manual file. Here, the input is the electronic file of the work manual selected by the user, and the output is the file stored on the server.

[1306] Step 2: Analyze the contents of the operational manual

[1307] The server analyzes the received business manual file. First, the server converts the file into text data, and then uses a natural language processing module (e.g., spaCy or NLTK) to identify elements such as business procedures, roles, triggers, and conditions. The input here is the text data of the business manual stored on the server, and the output is the extracted elements such as business procedures and roles. Specifically, the process involves analyzing the text content, extracting keywords and phrases, and converting it into structured data.

[1308] Step 3: Generating the Requirements Definition Diagram

[1309] The server generates a requirements definition diagram using a flowchart drawing library (e.g., Graphviz) based on the extracted business processes and elements. The generated requirements definition diagram is displayed to the user via a web interface. The input here is the extracted business processes and elements, and the output is the requirements definition diagram. Specifically, the operation involves converting the extracted data into a visual flowchart and displaying it in a user-friendly format.

[1310] Step 4: Selecting the parts to be systematized

[1311] The user selects the part of the requirements diagram they want to automate via a web interface. For example, clicking on the "Inventory Update" process selects that part. The selected data is sent from the terminal to the server. The input here is the part of the requirements diagram selected by the user, and the output is the selected data sent to the server. Specifically, the operation involves clicking on a particular part of the interface to select the part to be automated.

[1312] Step 5: Detailed Analysis and Visualization

[1313] The server performs a detailed analysis of the selected portion and displays it to the user using a detailed visualization tool (e.g., D3.js). The input here is a portion of the requirements diagram selected by the user, and the output is the detailed analysis results and their visualization data. Specific operations include data analysis of the selected portion, generation of a detailed flowchart, and display on the interface.

[1314] Step 6: Calculating the time-saving effect

[1315] The server compares the contents of the work manual with the systematized process and calculates the time savings. This calculation uses a statistical algorithm (e.g., Scikit-learn in Python). The input is the analysis results of the work manual and the data of the systematized process, and the output is the calculated time savings. The specific operation includes comparing the time required for manual and systematized tasks, calculating the effect using statistical methods, and visualizing the results.

[1316] Step 7: Provide systemization solutions and programming methods.

[1317] The server proposes the optimal systemization solution based on the analysis results and user requirements. For example, it might suggest "using the inventory module of the ERP system." It also provides specific programming methods (code examples and programming procedures). The input here is the analysis results and user requirements, while the output is the proposed solution and programming method. Specific operations include evaluating the analysis results, selecting an appropriate solution, and providing specific programming procedures.

[1318] Step 8: Utilizing the Emotional Engine

[1319] While the user is interacting with the system, the emotion engine recognizes the user's emotional state and adjusts the interface accordingly. This emotion engine uses speech analysis (e.g., Google Speech-to-Text API) and text analysis (e.g., OpenAI's GPT). The input is the user's voice or text data, and the output is the emotion analysis results and the adjusted interface. Specific operations include real-time analysis of the user's voice and text, identification of emotional state, and dynamic adjustment of the interface.

[1320] (Application Example 2)

[1321] 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".

[1322] Traditional systemization processes based on operational manuals require manual analysis and requirements definition, which are extremely time-consuming and labor-intensive. This results in decreased productivity and makes it difficult to improve operational efficiency. Furthermore, the inability to adjust the interface and provide support based on user emotions makes it difficult to improve the user experience.

[1323] 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.

[1324] In this invention, the server includes means for uploading business manual files, means for analyzing the contents of the uploaded business manuals and extracting business processes and elements, means for generating a requirements definition diagram based on the extracted information, means for selecting parts to be systematized from the requirements definition diagram, means for analyzing the detailed requirements of the selected parts and displaying them with a visualization tool, means for comparing the business manual with the systematized process and calculating the time reduction effect, means for providing a systematization solution and specific programming methods, and means for adjusting the interface and support according to the user's emotional state using an emotion engine that recognizes the user's emotions. As a result, the analysis and systematization of business manuals are automated, significantly reducing labor and time, while enabling flexible support that responds to the user's emotions.

[1325] A "business manual" is a document that contains detailed explanations of specific business procedures, roles, triggers, and conditions.

[1326] "Method of uploading" refers to the function or interface that allows users to send work manual files from their terminal to the server.

[1327] The "means of analysis" refer to a function that converts the content of uploaded business manuals into text data and extracts business processes and elements using natural language processing technology.

[1328] A "requirements definition diagram" is a diagram that visually represents the flow and process of business operations, making it easy for users to understand.

[1329] "Systematizing" refers to automating business processes that were previously performed manually and improving efficiency through the use of software and systems.

[1330] A "visualization tool" is a tool or interface used to visually display analyzed data or process flows.

[1331] "Time-saving effect" refers to the amount of time saved by systematizing tasks compared to traditional manual processes.

[1332] A "systemization solution" refers to a combination of software frameworks and APIs optimized for automating specific business processes.

[1333] "Programming method" refers to the implementation method of a program, including specific procedures and sample code for systemization.

[1334] An "emotion engine" is a technology that recognizes a user's emotional state through voice and text analysis, and adjusts the interface and support based on the results.

[1335] An "interface" refers to the screen display and means of operation that a user uses to interact with a system.

[1336] "Support" refers to the guidance and supplementary information provided to users when using a system.

[1337] This invention aims to efficiently systematize operations based on the operation manuals for robots used in factories. In particular, it describes a system that provides information to the user visually using smart glasses and provides support tailored to the user's state using an emotion engine.

[1338] Uploading and analyzing business manuals

[1339] First, the user uploads the robot operation manual from their device to the server via smart glasses. Using the smart glasses' user interface, they select the manual file and send it to the cloud server. The server receives the uploaded manual and converts it into text data. The software used here includes a natural language processing (NLP) module, which extracts work procedures, roles, and other relevant information.

[1340] Generation of Requirements Definition Diagrams

[1341] The server automatically generates a requirements definition diagram based on the extracted business processes and elements. This process uses a flowchart generation library to visually represent the business flow. The generated requirements definition diagram is displayed on the smart glasses screen.

[1342] Selection and analysis of the systematization components

[1343] Users select the parts they want to systemize from a requirements definition diagram using smart glasses. The selected data is sent from the terminal to the server, which then performs a detailed analysis of that part. During this process, a detailed process flow is displayed using a visualization tool.

[1344] Calculation of time-saving effect

[1345] The server compares the contents of the operational manual with the systematized process and calculates the time-saving effect using a statistical algorithm. The calculation results are visualized and presented to the user.

[1346] Providing system solutions and programming methods.

[1347] Furthermore, the server proposes the optimal systemization solution based on the analysis results and user selections. This includes specific software frameworks, API usage methods, and sample code. This enables efficient implementation.

[1348] Utilizing the Emotion Engine

[1349] When a user uses smart glasses, the emotion engine recognizes the user's emotional state through voice and text analysis. For example, if the user is confused, the system provides a detailed explanation. The interface is also adjusted and support messages are provided according to the emotional state.

[1350] Specific example

[1351] For example, a new factory operator uploads a robot initial setup manual to smart glasses. The system extracts the robot operation procedures and generates an initial setup flowchart. The operator follows the flowchart displayed on the smart glasses, performing the operations step by step. If there are any questions, the glasses' emotion engine detects the operator's confusion and automatically displays detailed explanations or video tutorials. This allows even inexperienced operators to set up the robot with confidence.

[1352] Example of a prompt

[1353] Please describe the entire process of a system that automatically generates requirements definition diagrams from factory robot operation manuals and displays them to users using smart glasses, and provide a concrete example of how to use an emotion engine for user support.

[1354] This invention automates the analysis and systematization of business manuals, resulting in a significant reduction in labor and time, while also enabling flexible support tailored to the user's needs.

[1355] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1356] Step 1:

[1357] Uploading the business manual

[1358] The user selects a robot operation manual file using the user interface of the smart glasses and presses the upload button. This sends the selected manual file from the terminal (smart glasses) to the server.

[1359] Input: Business manual file

[1360] Output: Business manual file uploaded to the server

[1361] Step 2:

[1362] Analysis of business manuals

[1363] The server receives the uploaded business manual file and converts its contents into text data. A natural language processing (NLP) module is used to extract business processes and elements (procedures, roles, triggers, conditions, etc.).

[1364] Input: Uploaded business manual file

[1365] Output: Extracted business processes and elements

[1366] Step 3:

[1367] Generation of Requirements Definition Diagrams

[1368] The server uses a flowchart generation library to automatically generate requirements definition diagrams based on the extracted business processes and elements. The generated requirements definition diagrams are saved in the cloud and displayed on smart glasses.

[1369] Input: Extracted business processes and elements

[1370] Output: Requirements definition diagram

[1371] Step 4:

[1372] Selection of Systematization Components

[1373] The user selects the parts of the requirements diagram they want to automate through the display interface of their smart glasses. The selected data is then sent from the device to the server.

[1374] Input: Requirements definition diagram

[1375] Output: Selected systemization portion

[1376] Step 5:

[1377] Detailed analysis and visualization

[1378] The server analyzes the selected system components in detail and generates a detailed process flow. The generated flow is then displayed to the user in an easy-to-understand format using a visualization tool.

[1379] Input: Selected systemization portion

[1380] Output: Detailed process flow

[1381] Step 6:

[1382] Calculation of time-saving effect

[1383] The server compares the contents of the operational manual with the systematized process and uses a statistical algorithm to calculate the time savings. The calculation results are visualized and displayed on smart glasses.

[1384] Input: Detailed process flow

[1385] Output: Calculation results of time reduction effect

[1386] Step 7:

[1387] Providing system solutions and programming methods.

[1388] The server proposes the optimal systemization solution based on the analysis results and user requests. Furthermore, it provides specific program sample code and instructions on how to use the API.

[1389] Input: Calculation result of time reduction effect

[1390] Output: Systematized solution and specific program steps

[1391] Step 8:

[1392] Utilizing the Emotion Engine

[1393] When a user uses smart glasses, the emotion engine recognizes the user's emotional state through voice analysis and eye tracking. For example, if the user is confused, the system displays a detailed explanation or video tutorial.

[1394] Input: User sentiment data

[1395] Output: Interface adjustments and support information tailored to user sentiment.

[1396] 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.

[1397] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1398] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1399] 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.

[1400] 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.

[1401] 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.

[1402] 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.

[1403] 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 based, for example, 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.

[1404] 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."

[1405] 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.

[1406] 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.

[1407] 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.

[1408] 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.

[1409] 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.

[1410] 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.

[1411] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a ...

Claims

1. Methods for uploading business manual files, A means to analyze the contents of uploaded business manuals and extract business processes and elements, A means of generating a requirements definition diagram based on the extracted information, A method for selecting the parts to be systematized from the requirements definition diagram, A means of analyzing the detailed requirements of the selected portion and displaying them using a visualization tool, A method for comparing the operational manual with the systemized process and calculating the time reduction effect, Means for providing systemization solutions and specific programming methods, A system that includes this.

2. The system according to claim 1, wherein the means for analyzing the contents of the business manual is to identify business procedures, roles, triggers, and conditions using a natural language processing module.

3. The system according to claim 1, wherein the means for calculating the time reduction effect is to compare the results of the analysis of the work manual with the data of the systemized process and calculate the time reduction using a statistical algorithm.

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