system

Abstract

Provide a system. 【Solution means】 Means for obtaining screen display data from a user terminal, Means for analyzing the obtained screen display data and identifying business procedures, Means for visualizing the identified business procedures and generating a current business flow, Means for analyzing the business flow to identify areas for improvement, Means for designing an optimized business flow based on the identified areas for improvement, Means for automatically generating an AI agent based on the optimized business flow, Means for distributing the generated AI agent to the user terminal, A system including the above.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In white-collar operations, it is important to identify inefficient business processes and improve efficiency. However, it is difficult to determine which operations should be improved, and there is often a lack of specialized knowledge and resources for developing AI agents for efficiency improvement. As a result, there is a problem of missing opportunities for business efficiency improvement and wasting time and effort. 【Means for Solving the Problems】 【0005】 This invention generates a current workflow by analyzing screen display data acquired from a user terminal to identify and visualize business procedures. It then identifies areas for improvement through analysis of the workflow and designs an optimized workflow. Furthermore, it automatically generates an AI agent based on the optimized workflow and distributes it to the user terminal, thereby achieving practical AI-driven business efficiency improvements even in situations where specialized skills are lacking. 【0006】 A "user terminal" is a computing device used by a user when performing their work, and is a device that can acquire screen display data. 【0007】 "Screen display data" refers to digital data captured from information displayed on the user's terminal, including user actions and application operation status. 【0008】 "Business procedures" refer to a series of operations and processes that a user performs in order to carry out a specific task. 【0009】 A "business process flow" is a visual representation of business procedures, showing the overall picture of the process. 【0010】 "Room for efficiency improvements" refers to identifying unnecessary steps or areas for improvement within business procedures and workflows. 【0011】 An "optimized workflow" refers to a more efficient set of work procedures and processes that have been redesigned with potential for further efficiency improvements in mind. 【0012】 An "AI agent" is a software program designed to automatically perform the work procedures that a user would normally do. [Brief explanation of the drawing] 【0013】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] 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 Example 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 Example 2 when an 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 an emotion engine is combined. 【Mode for Carrying Out the Invention】 【0014】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described according to the accompanying drawings. 【0015】 First, the terms used in the following description will be explained. 【0016】 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. 【0017】 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. 【0018】 In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc. 【0019】 In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc. 【0020】 <00,00107>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." 【0021】 [First Embodiment] 【0022】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0023】 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. 【0024】 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). 【0025】 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. 【0026】 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. 【0027】 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. 【0028】 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. 【0029】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0030】 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. 【0031】 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. 【0032】 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. 【0033】 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". 【0034】 To implement the present invention, a system comprising the following components is required. First, the user performs their daily tasks on a terminal with a dedicated application installed. When the user starts work, they launch an application with a recording function and record the PC screen. The recording captures the user's operations, application launch, visual information, etc., in chronological order. 【0035】 The terminal uploads the recorded data to the server. The server receives this recorded data and performs a detailed analysis using machine learning techniques. First, it recognizes patterns in the operations within the recorded data and extracts the business procedures. Next, the server analyzes these procedures and identifies details related to each step. Based on this data, it visualizes the current business flow. 【0036】 Once the workflow visualization is complete, the server analyzes the workflow and identifies areas where efficiency can be improved. For example, if it includes repetitive data entry or processing tasks, these are recognized as areas for improvement. Based on this information, the server redesigns the workflow for optimization and proposes improvements. 【0037】 The server automatically generates corresponding AI agents based on optimized workflows. These AI agents aim to mimic user procedures and automate specific operations. The generated AI agents are then distributed to user terminals. 【0038】 As a concrete example, consider data entry work. Assume a user is opening multiple spreadsheets and manually entering information. This process is recorded, and the server analyzes the screen capture data. If a series of steps related to data entry are identified and many repetitions are found within that process, the server proposes automating those repetitive tasks. An AI agent is then generated, allowing the agent to perform the data entry task on behalf of the user in the future. 【0039】 Thus, the system of the present invention provides a method for refining business processes and achieving a high level of efficiency by consistently performing everything from user business analysis to automation. 【0040】 The following describes the processing flow. 【0041】 Step 1: 【0042】 Before the user begins working on their PC, they launch a dedicated recording application and start recording the PC screen. This ensures that all operations performed during the work are recorded as video data. 【0043】 Step 2: 【0044】 When the device stops recording, the recorded data is automatically uploaded to the server. The data includes the user's operation history and details of the active window. 【0045】 Step 3: 【0046】 The server receives the recorded data and applies machine learning algorithms to analyze the work procedures. Specifically, it analyzes mouse click patterns and keyboard inputs to identify which actions belong to which work procedures. 【0047】 Step 4: 【0048】 The server visualizes the current business flow (As-Is) based on the analysis results. This allows users to visually confirm their own business processes. 【0049】 Step 5: 【0050】 The server further analyzes the workflow and identifies areas within the work process where efficiency can be improved. In particular, it focuses on repetitive and time-consuming steps. 【0051】 Step 6: 【0052】 The server designs an optimized workflow (To-Be) based on areas for improvement and generates improvement suggestions. These suggestions include eliminating unnecessary steps and automating processes. 【0053】 Step 7: 【0054】 The server automatically generates corresponding AI agents based on optimized workflows. These agents are designed with scripts to automatically process specific steps. 【0055】 Step 8: 【0056】 The generated AI agent is distributed to the user's device, and the environment for automating business processes is established. 【0057】 Step 9: 【0058】 The AI ​​agent mimics user actions and automatically executes specified work procedures, saving users time and effort. 【0059】 (Example 1) 【0060】 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." 【0061】 In today's work environment, many tasks involve cumbersome and repetitive procedures that hinder efficient work. Users face the challenge of having to spend a significant amount of time and effort manually. Furthermore, there are limits to manually streamlining existing processes, necessitating more sophisticated automation technologies. 【0062】 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. 【0063】 In this invention, the server includes means for acquiring recorded data from a user terminal, means for analyzing the acquired recorded data and identifying an operation procedure, means for visualizing the identified operation procedure and generating the current operation process, means for analyzing the operation process and identifying areas for improvement, means for automatically generating an intelligent agent based on the optimized operation process, and means for transmitting the generated intelligent agent to the user terminal. This enables automation to improve business efficiency. 【0064】 An "information processing device" is a computer system used to record user operations and is a device that collects and stores data. 【0065】 "Recorded data" refers to a collection of digital information that records user actions and changes on the screen in chronological order. 【0066】 "Operation procedure" refers to a series of user operations or processes performed to carry out a specific task. 【0067】 "Visualization" is the process of representing extracted operational steps in the form of flowcharts or process maps, making them intuitively understandable. 【0068】 "Operation process" refers to a visual representation of the steps and procedures involved in carrying out a task. 【0069】 "Room for improvement" refers to parts of the current business process that have the potential to reduce or improve repetitive or inefficient steps. 【0070】 An "intelligent agent" is a program that uses artificial intelligence technology to mimic user actions and automate specific work procedures. 【0071】 "User terminal" refers to a computer or other digital device used by a user to perform their duties. 【0072】 This invention is an automated system designed to improve user work efficiency. Users record their daily operations using a terminal with a dedicated application installed. The terminal transmits the recorded data to a server via the internet. This recorded data includes the user's manual actions and changes on the screen. 【0073】 The server receives this recorded data and analyzes it using a machine learning model. Specifically, it recognizes patterns in user operations within the data and extracts business procedures. The hardware used for this analysis is a server device capable of high-speed processing, and the software implements machine learning algorithms for pattern recognition and data analysis. 【0074】 Once the analysis is complete, the server visually represents the business procedures as flowcharts and process maps, generating a business flow. Next, the business flow is examined in detail to identify repetitive tasks and parts that can be automated. This leads to increased efficiency in business operations. 【0075】 The server automatically generates intelligent agents based on optimized workflows. These agents mimic the steps the user was performing and automatically execute specific operations. The generated agents are then distributed to the user's terminal. 【0076】 As a concrete example, consider a scenario where a user manually enters multiple data sets into different formats every day. By recording this process, the server analyzes the data entry steps and identifies repetitive operations. An intelligent agent is then generated, and in subsequent instances, this data entry can be automated by the agent, significantly reducing the user's time and effort. 【0077】 An example of a prompt to input into the generating AI model is: "Analyze the recorded PC screen data and extract the user's work procedures. Next, identify repetitive tasks and parts that can be automated, and design the optimal workflow." This prompt helps the system create efficient work processes based on the user's needs. 【0078】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0079】 Step 1: 【0080】 The user installs a dedicated application on their device and begins their daily work. At the start of their workday, the user activates the application's recording function to record their PC screen. In this process, work operation information is used as user input, and the output is recorded data. During recording, the user proceeds with their work as usual, so all operations during that time are recorded chronologically. 【0081】 Step 2: 【0082】 After recording is complete, the device uploads the recorded data to the server. During this process, the device transmits the data over the network, and the server receives it. The input is the recorded data, and the server can acquire this data as output. The upload process includes checking the approximate file size and communication speed, as well as a retransmission function in case of errors. 【0083】 Step 3: 【0084】 The server analyzes the acquired video data. First, it uses a machine learning algorithm to recognize patterns in user actions from the data. This analysis extracts business procedures. Video data is used as input, and patterned business procedures are generated as output. Specifically, it analyzes the frequency and order of clicks and input operations to identify standard procedures. 【0085】 Step 4: 【0086】 The server visualizes the extracted business procedures. This visualization represents the workflow as a flowchart or process map, making it intuitively understandable. The visualization requires business procedure data as input, and the output is a clear and easy-to-understand visual representation of the business processes. This allows users and administrators to efficiently grasp the current workflow. 【0087】 Step 5: 【0088】 The server analyzes areas for efficiency improvements based on the visualized workflow. If there are repetitive operations or time-consuming steps within the workflow, they are identified as targets for automation. The visualized workflow is used as input, and areas for improvement are identified as output. This allows for the discovery of potential areas for optimization. 【0089】 Step 6: 【0090】 The server automatically generates intelligent agents based on areas for improvement. Identified business procedures are used as input for generation, and agents that automate specific operations are output. These intelligent agents mimic repetitive user actions using machine learning models, thereby improving operational efficiency. 【0091】 Step 7: 【0092】 The server sends the generated intelligent agent to the user's terminal. The agent's input includes an automation script, and its output allows the agent to be executed on the user's terminal. This allows the user to experience tasks automated by the agent, improving work efficiency. 【0093】 (Application Example 1) 【0094】 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." 【0095】 Improving the efficiency of work procedures is a crucial issue in modern industrial settings. However, many manual tasks are repetitive and inefficient. In particular, physical work procedures in factories are difficult to record on-site and rely on human visual judgment, resulting in insufficient data collection and analysis for efficiency improvements. Therefore, there is a need to improve the efficiency of work procedures using on-site visual information. 【0096】 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. 【0097】 In this invention, the server includes means for acquiring visual information from a user device, means for analyzing the acquired visual information and identifying work procedures, and means for visualizing the identified work procedures and generating current work procedures. This makes it possible to efficiently analyze and optimize work procedures using on-site visual information. 【0098】 A "user device" is a device operated by the user and is a terminal equipped with an interface for acquiring visual information. 【0099】 "Visual information" refers to image data and video data acquired by user devices, and is information used to record work procedures and operating methods. 【0100】 A "work procedure" is a sequence of operations and actions necessary to perform a specific task. 【0101】 "Visualization" refers to illustrating acquired work procedures and displaying them in an easy-to-understand format, thereby enabling intuitive understanding of business flows and procedures. 【0102】 An "AI role" is a role created by artificial intelligence for the purpose of streamlining work procedures, and is a program designed to automatically perform specific tasks. 【0103】 "Transmission" refers to the process of delivering AI roles to user devices, and involves transmitting data using electronic means. 【0104】 The system for implementing this invention mainly consists of a user device and a server. 【0105】 The user device is a terminal equipped with video acquisition capabilities, similar to smart glasses, that collects visual information of work procedures in the work environment. When the user performs a task, the relevant work procedure is recorded by the user device. The recorded visual information is uploaded from the user device to the server. 【0106】 The server provides a cloud environment for data analysis, using machine learning frameworks such as Python and TENSORFLOW® to analyze acquired visual information. Specifically, it recognizes behavioral patterns and identifies work procedures, visualizing workflows based on these findings. This visualized information forms the basis for evaluating the potential for work efficiency improvements. Based on the acquired information, the server has the capability to identify tasks that can be streamlined and generate appropriate AI roles. These AI roles are designed to automate specific tasks and are transmitted to user devices. 【0107】 As a concrete example, consider optimizing a series of assembly steps in a production line. Video data recorded by smart glasses is analyzed on a server to visualize a single work step. The analysis identifies screw tightening as a repetitive task and proposes automation using AI. The AI's role is then concretely defined as control commands for a screw-tightening robot. 【0108】 An example of a prompt for the generated AI model would be, "Analyze the factory assembly procedure from visual information and identify the parts that can be automated." 【0109】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0110】 Step 1: 【0111】 The user puts on smart glasses and begins working. Video data of the work procedure is recorded in real time on the device. Visual information is recorded as input data during this process. 【0112】 Step 2: 【0113】 The device uploads recorded visual information to a server via the internet. The visual information data becomes input to the server. At this point, the data is converted to an appropriate format and becomes ready for analysis on the server side. 【0114】 Step 3: 【0115】 The server analyzes the received visual information data. Using Python and TensorFlow, it performs pattern recognition on actions within the video and data calculations to identify work procedures. This identifies the dynamic flow and repetitive actions of the work, and outputs structured procedure data. 【0116】 Step 4: 【0117】 The server visualizes the identified work procedures. A visualized workflow is generated, preparing data to evaluate potential for efficiency improvements. This output is provided as a visualized flowchart or graph. 【0118】 Step 5: 【0119】 The server determines which tasks can be made more efficient based on the visualized information. Repetitive actions and simple tasks are identified as candidates for automation. This step provides a list of tasks that can be optimized and their details as output. 【0120】 Step 6: 【0121】 The server generates an AI role using a generated AI model based on the identified tasks. The AI ​​role is created as a set of instructions or scripts to execute the corresponding automation task, utilizing prompts appropriate to the current input data. The generated AI role is intended to execute specific automation steps. 【0122】 Step 7: 【0123】 The generated AI role is sent back to the terminal. The user's device receives this AI role and uses it to automate the actual work. The user receives support for the automated work provided by the AI ​​role, improving work efficiency. 【0124】 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. 【0125】 To implement this invention, a system integrating a dedicated recording application and an emotion engine is installed on the user terminal. When the user starts work, the recording application is launched and the PC screen recording begins. This records the user's operations and activities on the PC in real time. 【0126】 The terminal uploads the recorded data to the server. The server uses machine learning algorithms to analyze the recorded data and extract business procedures. Based on the analysis results, it performs process mapping and generates the current business flow. Furthermore, the server analyzes this business flow and considers possibilities for efficiency improvements. 【0127】 Furthermore, an emotion engine built into the user terminal analyzes the user's facial expressions, voice, and operation patterns to acquire emotional information. The emotion engine recognizes the user's emotional state and can measure, for example, stress levels and concentration levels. This makes it possible to monitor how the user's emotions change within the workflow. 【0128】 The server can adjust workflows based on data from the emotion engine. For example, if it detects that a user is experiencing stress, it will provide suggestions for optimizing their work accordingly. This allows users to perform their tasks more comfortably. 【0129】 Furthermore, AI agents are automatically generated based on optimized workflows and distributed to user terminals. These AI agents automatically perform repetitive tasks that users would normally do, reducing their workload. 【0130】 As a concrete example, consider data entry tasks. In a scenario where a user uses multiple spreadsheet programs to input standardized data, the emotion engine detects fatigue from the user's facial expressions. Based on this information, the server identifies parts of the workflow that can be made more efficient, and the AI ​​agent automates part of the data entry, thereby reducing the user's burden. 【0131】 This system provides an advanced method for simultaneously improving operational efficiency and enhancing the user's work experience. 【0132】 The following describes the processing flow. 【0133】 Step 1: 【0134】 Before the user begins work, the recording application on the terminal is launched and screen recording begins. Simultaneously, an emotion engine starts operating to monitor the user's facial expressions and voice. 【0135】 Step 2: 【0136】 The device records the user's PC screen and emotional data in real time. The recorded data includes detailed operations such as mouse movements, keyboard input, and application switching. The emotional engine uses the camera and microphone to continuously analyze the user's facial movements and voice tone. 【0137】 Step 3: 【0138】 After work hours, the terminal uploads video recordings and emotion data to the server. This allows the server to centrally receive both datasets. 【0139】 Step 4: 【0140】 The server analyzes the uploaded data. For recorded video data, machine learning techniques are used to extract and systematize work procedures. Emotional data is also analyzed to understand the user's emotional state at each step of the work process. 【0141】 Step 5: 【0142】 The server visualizes the workflow and maps the current workflow (As-Is) along with changes in the user's emotional state. This allows for understanding emotional fluctuations at each step. 【0143】 Step 6: 【0144】 The server analyzes the workflow and simultaneously evaluates areas for improvement and user stress. For example, it identifies steps where users are losing focus and suggests ways to streamline those steps. 【0145】 Step 7: 【0146】 Based on efficiency suggestions, the server redesigns business procedures and generates an optimized workflow (To-Be). The redesigned procedures also take into account improvements to the user's emotional state. 【0147】 Step 8: 【0148】 The server automatically generates AI agents based on optimized workflows. Before distributing the generated agents to users, simulation tests are performed to ensure they function correctly. 【0149】 Step 9: 【0150】 The generated AI agent is distributed to the user's terminal and applied to subsequent tasks. The AI ​​agent mimics the user's procedures to perform automation, reducing the user's workload. 【0151】 (Example 2) 【0152】 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 will be referred to as the "terminal." 【0153】 While streamlining user procedures in business operations is crucial, traditional methods only partially optimize workflows and fail to consider user emotional burden and psychological stress. Furthermore, generating and distributing automated agents that reflect streamlined workflows presents challenges. Addressing these issues is essential. 【0154】 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. 【0155】 In this invention, the server includes means for acquiring display information from a user terminal, means for analyzing the acquired display information and identifying business procedures, and means for analyzing the user's emotional state and using the emotional information to optimize the flow of activities. This simultaneously achieves increased efficiency in the business flow and reduced emotional burden on the user, and further enables the generation and distribution of automated agents based on the more efficient flow. 【0156】 A "user terminal" is a computer device used by a user, capable of displaying and manipulating data. 【0157】 "Displayed information" refers to digital data displayed on the screen of a user's terminal, and includes some of the information necessary for business operations. 【0158】 A "business procedure" is a sequence of operations and steps that must be followed to perform a specific task. 【0159】 An "activity flow" is a visual representation of business procedures, a diagrammatic representation that shows the structure of the current business process. 【0160】 An "intelligent agent" is a software program created to automate business processes and has the ability to automatically perform repetitive tasks. 【0161】 "Emotional information" refers to data that indicates a user's emotional state, and is psychological information extracted from facial expressions and voice. 【0162】 This invention provides a system that improves work efficiency while reducing the emotional burden on users operating user terminals. The main components of the system are a recording application installed on the user terminal, an emotion analysis engine, and a server for processing this data. 【0163】 User: 【0164】 When a user begins work, they launch a recording application on their terminal. This recording application captures the information displayed on the user's PC screen and collects digital data, including the terminal's operation status. This operation is performed using a standard PC or laptop. 【0165】 Terminal: 【0166】 The emotion analysis engine installed in the device captures facial expressions and voice in real time using the user's video camera and microphone, and extracts the user's emotional information. This allows for the evaluation of stress levels and concentration levels during actual work. The device also uploads the recorded video and emotional data to a server at predetermined intervals. 【0167】 server: 【0168】 The server first analyzes the business procedures using the uploaded data. Next, it generates a current business flow based on the analysis results and visualizes that flow in detail. The server then identifies parts of the business flow that can be made more efficient and proposes ways to optimize the activity flow while taking into account user sentiment information. After optimization is complete, the server automatically generates an intelligent agent and distributes it to the user's terminal. This agent reduces the user's workload by automatically performing repetitive tasks. 【0169】 Specific example: 【0170】 As a concrete example, consider a scenario where a user spends more than three hours using multiple spreadsheet programs for data entry. In this case, we propose a method where an emotion analysis engine detects fatigue from the user's facial expressions, and a server automates part of the task using an intelligent agent to reduce the burden. 【0171】 Example of a prompt: 【0172】 "How can we monitor users' emotional changes during work, analyze their stress levels, and optimize workflows?" 【0173】 This invention makes it possible to improve both operational efficiency and user satisfaction simultaneously. 【0174】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0175】 Step 1: 【0176】 The user launches a recording application on their device. The input is the information displayed on the user's PC screen. The recording application uses this input to capture digital data of the screen in real time. As a result, the device outputs the user's actions and display status as a video file. 【0177】 Step 2: 【0178】 The device uses an emotion analysis engine to capture the user's facial expressions and voice. The input consists of the user's video and audio data. Based on this, the emotion analysis engine extracts the user's emotional information and outputs stress levels and concentration levels as numerical data. 【0179】 Step 3: 【0180】 The device uploads recorded video data and emotion information to the server. The input consists of recorded video data and emotion information. The device sends the data to the server using a secure protocol and outputs a notification when the upload is complete. 【0181】 Step 4: 【0182】 The server analyzes the received video data. The input is video data of the screen display. The server uses a machine learning algorithm to identify business procedures and perform process mapping. The output is a list of identified business procedures and their visualization information. 【0183】 Step 5: 【0184】 The server optimizes business workflows based on received emotional information. Its inputs include emotional information and business procedures. The server generates efficiency suggestions based on the emotional state and designs an optimized workflow. The output consists of the optimization suggestions and the improved workflow. 【0185】 Step 6: 【0186】 The server automatically generates intelligent agents based on optimized business workflows. The input is an optimized business workflow. The server utilizes an AI model to develop agents for business automation and outputs agent files. 【0187】 Step 7: 【0188】 The server distributes the generated intelligent agent to the user terminal. The input is the agent file. The server completes the distribution process and receives output notifying the user that the agent is ready to use. 【0189】 (Application Example 2) 【0190】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0191】 This invention aims to solve the problem of providing a system that simultaneously improves operational efficiency and manages the emotional state of workers in production sites. In particular, there is a need for operational efficiency improvements that take into account the emotional state of workers, which has not been fully captured by conventional methods for optimizing workflows. 【0192】 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. 【0193】 In this invention, the server includes means for acquiring information from a user terminal, means for monitoring the emotional state of an employee using emotion analysis means, and means for adjusting the workflow based on emotional information. This makes it possible to optimize the workflow while taking into account the emotional state of the employee. 【0194】 A "user terminal" is an electronic device used by a user to retrieve or display information. 【0195】 "Means of acquiring information" refers to methods and devices for collecting necessary data from user terminals. 【0196】 "Means for identifying business procedures" refers to methods or devices for identifying specific business procedures based on acquired information. 【0197】 "Means for generating business process flows" refers to methods or devices for visually creating a business process flow based on identified business procedures. 【0198】 "Means for identifying areas for efficiency improvement" refer to methods and devices for analyzing business workflows and finding areas that can be improved. 【0199】 "Means for designing optimized business workflows" refers to methods or devices for restructuring business workflows based on identified areas for improvement. 【0200】 "Means for automatically generating AI agents" refers to methods or devices for automatically creating artificial intelligence agents according to an optimized workflow. 【0201】 "Means for distributing generated AI agents" refers to methods or devices for sending and installing the created AI agents on user terminals. 【0202】 "Emotional analysis means" refers to methods and devices for extracting and analyzing emotional information from a worker's facial expressions and actions. 【0203】 "Means for adjusting business processes based on emotional information" refers to methods or devices for changing the flow of business processes to an optimal state based on acquired emotional information. 【0204】 To implement this invention, a system is first required to acquire information from a user terminal. This system records user operations and sends the data to a server. The server has a high-performance processor and implements machine learning algorithms for data analysis. Machine learning frameworks such as TensorFlow or PyTorch can be used for this analysis. This allows for the identification of business procedures, and this information is used to visually generate a business flow. 【0205】 Next, in order to use emotion analysis, the user terminal needs to be equipped with a camera and sensors capable of facial recognition and motion analysis. OpenCV and Affectiva technologies can be used for this. The server uses this emotion data to collect emotional information and use it to redesign the workflow. 【0206】 Furthermore, on the server, areas for efficiency improvements are identified, and optimized workflows are designed. Based on this design, an AI agent is automatically generated. This AI agent is then immediately distributed to user terminals and automatically executes the necessary business procedures. 【0207】 As a concrete example of this embodiment, consider a process on a production line with a high defect rate. If the emotion analysis means detects a high stress level in the worker, it re-evaluates the workflow of that process and proposes reducing stress and lowering the defect rate by having the AI ​​agent automate some of the tasks. 【0208】 An example of a prompt message is, "In a factory production line, analyze the factors causing a decrease in work efficiency at a specific process, and generate improvement suggestions based on sentiment data." In this way, it becomes possible to improve both work efficiency and the morale of the workers. 【0209】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0210】 Step 1: 【0211】 The user terminal uses a camera and sensors to capture the worker's facial expressions and movements. This input data is converted into emotional information using a facial recognition algorithm. The output provides the worker's stress level and concentration level. 【0212】 Step 2: 【0213】 The user terminal records real-time operation data and work status, and sends this data to the server. Input data includes keystrokes, mouse movements, and screen display content. The server analyzes this data to identify work procedures and generates a workflow as output. 【0214】 Step 3: 【0215】 The server analyzes the generated business flow using a machine learning algorithm to identify areas for improvement to enhance efficiency. The input is the generated business flow, and the output is the identified areas for efficiency improvement. 【0216】 Step 4: 【0217】 The server designs new workflows and automatically generates AI agents based on the identified areas for improvement. This automated generation process utilizes a generative AI model. The input is information about areas for improvement, and the output is the automatically generated AI agent. 【0218】 Step 5: 【0219】 The server distributes and deploys the generated AI agents to user terminals. The AI ​​agents automatically execute the user's standard work procedures, reducing their workload. The output is the automated business process. 【0220】 Step 6: 【0221】 The server continuously receives feedback from the user terminal and optimizes the AI ​​agent's operation. The input is user feedback information, and the output is the improved AI agent. 【0222】 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. 【0223】 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. 【0224】 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. 【0225】 [Second Embodiment] 【0226】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0227】 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. 【0228】 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). 【0229】 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. 【0230】 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. 【0231】 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). 【0232】 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. 【0233】 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. 【0234】 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. 【0235】 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. 【0236】 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. 【0237】 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". 【0238】 To implement the present invention, a system comprising the following components is required. First, the user performs their daily tasks on a terminal with a dedicated application installed. When the user starts work, they launch an application with a recording function and record the PC screen. The recording captures the user's operations, application launch, visual information, etc., in chronological order. 【0239】 The terminal uploads the recorded data to the server. The server receives this recorded data and performs a detailed analysis using machine learning techniques. First, it recognizes patterns in the operations within the recorded data and extracts the business procedures. Next, the server analyzes these procedures and identifies details related to each step. Based on this data, it visualizes the current business flow. 【0240】 Once the workflow visualization is complete, the server analyzes the workflow and identifies areas where efficiency can be improved. For example, if it includes repetitive data entry or processing tasks, these are recognized as areas for improvement. Based on this information, the server redesigns the workflow for optimization and proposes improvements. 【0241】 The server automatically generates corresponding AI agents based on optimized workflows. These AI agents aim to mimic user procedures and automate specific operations. The generated AI agents are then distributed to user terminals. 【0242】 As a concrete example, consider data entry work. Assume a user is opening multiple spreadsheets and manually entering information. This process is recorded, and the server analyzes the screen capture data. If a series of steps related to data entry are identified and many repetitions are found within that process, the server proposes automating those repetitive tasks. An AI agent is then generated, allowing the agent to perform the data entry task on behalf of the user in the future. 【0243】 Thus, the system of the present invention provides a method for refining business processes and achieving a high level of efficiency by consistently performing everything from user business analysis to automation. 【0244】 The following describes the processing flow. 【0245】 Step 1: 【0246】 Before the user begins working on their PC, they launch a dedicated recording application and start recording the PC screen. This ensures that all operations performed during the work are recorded as video data. 【0247】 Step 2: 【0248】 When the device stops recording, the recorded data is automatically uploaded to the server. The data includes the user's operation history and details of the active window. 【0249】 Step 3: 【0250】 The server receives the recorded data and applies machine learning algorithms to analyze the work procedures. Specifically, it analyzes mouse click patterns and keyboard inputs to identify which actions belong to which work procedures. 【0251】 Step 4: 【0252】 The server visualizes the current business flow (As-Is) based on the analysis results. This allows users to visually confirm their own business processes. 【0253】 Step 5: 【0254】 The server further analyzes the workflow and identifies areas within the work process where efficiency can be improved. In particular, it focuses on repetitive and time-consuming steps. 【0255】 Step 6: 【0256】 The server designs an optimized workflow (To-Be) based on areas for improvement and generates improvement suggestions. These suggestions include eliminating unnecessary steps and automating processes. 【0257】 Step 7: 【0258】 The server automatically generates corresponding AI agents based on optimized workflows. These agents are designed with scripts to automatically process specific steps. 【0259】 Step 8: 【0260】 The generated AI agent is distributed to the user's device, and the environment for automating business processes is established. 【0261】 Step 9: 【0262】 The AI ​​agent mimics user actions and automatically executes specified work procedures, saving users time and effort. 【0263】 (Example 1) 【0264】 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." 【0265】 In today's work environment, many tasks involve cumbersome and repetitive procedures that hinder efficient work. Users face the challenge of having to spend a significant amount of time and effort manually. Furthermore, there are limits to manually streamlining existing processes, necessitating more sophisticated automation technologies. 【0266】 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. 【0267】 In this invention, the server includes means for acquiring recorded data from a user terminal, means for analyzing the acquired recorded data and identifying an operation procedure, means for visualizing the identified operation procedure and generating the current operation process, means for analyzing the operation process and identifying areas for improvement, means for automatically generating an intelligent agent based on the optimized operation process, and means for transmitting the generated intelligent agent to the user terminal. This enables automation to improve business efficiency. 【0268】 An "information processing device" is a computer system used to record user operations and is a device that collects and stores data. 【0269】 "Recorded data" refers to a collection of digital information that records user actions and changes on the screen in chronological order. 【0270】 "Operation procedure" refers to a series of user operations or processes performed to carry out a specific task. 【0271】 "Visualization" is the process of representing extracted operational steps in the form of flowcharts or process maps, making them intuitively understandable. 【0272】 "Operation process" refers to a visual representation of the steps and procedures involved in carrying out a task. 【0273】 "Room for improvement" refers to parts of the current business process that have the potential to reduce or improve repetitive or inefficient steps. 【0274】 An "intelligent agent" is a program that uses artificial intelligence technology to mimic user actions and automate specific work procedures. 【0275】 "User terminal" refers to a computer or other digital device used by a user to perform their duties. 【0276】 This invention is an automated system designed to improve user work efficiency. Users record their daily operations using a terminal with a dedicated application installed. The terminal transmits the recorded data to a server via the internet. This recorded data includes the user's manual actions and changes on the screen. 【0277】 The server receives this recorded data and analyzes it using a machine learning model. Specifically, it recognizes patterns in user operations within the data and extracts business procedures. The hardware used for this analysis is a server device capable of high-speed processing, and the software implements machine learning algorithms for pattern recognition and data analysis. 【0278】 Once the analysis is complete, the server visually represents the business procedures as flowcharts and process maps, generating a business flow. Next, the business flow is examined in detail to identify repetitive tasks and parts that can be automated. This leads to increased efficiency in business operations. 【0279】 The server automatically generates intelligent agents based on optimized workflows. These agents mimic the steps the user was performing and automatically execute specific operations. The generated agents are then distributed to the user's terminal. 【0280】 As a concrete example, consider a scenario where a user manually enters multiple data sets into different formats every day. By recording this process, the server analyzes the data entry steps and identifies repetitive operations. An intelligent agent is then generated, and in subsequent instances, this data entry can be automated by the agent, significantly reducing the user's time and effort. 【0281】 Examples of prompt sentences input into the generation AI model include "Please analyze the recorded data of the PC screen and extract the user's business procedures. Next, identify repetitive operations and parts that can be automated, and design an optimal business flow." Based on this prompt, the system helps to realize an efficient business process based on the user's needs. 【0282】 The flow of the specific process in Example 1 will be described using FIG. 11. 【0283】 Step 1: 【0284】 The user installs a dedicated application on the terminal and starts daily work. When starting work, the user activates the recording function of the application and records the PC screen. In this process, operation information of the business is used as the user's input, and an output as recorded data is obtained. During recording, since the user proceeds with work as usual, all operations during that period are recorded in chronological order. 【0285】 Step 2: 【0286】 After the recording is completed, the terminal uploads the recorded data to the server. At this time, the terminal sends the data via the network, and the server receives the data. The input is the recorded data, and the server can obtain this data as the output. The upload process includes checking the approximate file size and communication speed, and a retransmission function when an error occurs. 【0287】 Step 3: 【0288】 The server analyzes the acquired recorded data. First, a machine learning algorithm is used to recognize the user's operation patterns from the data. Through this analysis, the business procedures are extracted. The recorded data is utilized as the input, and the patterned business procedures are generated as the output. Specifically, the frequency and order of clicks and input operations are analyzed to identify standard procedures. 【0289】 Step 4: 【0290】 The server visualizes the extracted business procedures. This visualization represents the workflow as a flowchart or process map, making it intuitively understandable. The visualization requires business procedure data as input, and the output is a clear and easy-to-understand visual representation of the business processes. This allows users and administrators to efficiently grasp the current workflow. 【0291】 Step 5: 【0292】 The server analyzes areas for efficiency improvements based on the visualized workflow. If there are repetitive operations or time-consuming steps within the workflow, they are identified as targets for automation. The visualized workflow is used as input, and areas for improvement are identified as output. This allows for the discovery of potential areas for optimization. 【0293】 Step 6: 【0294】 The server automatically generates intelligent agents based on areas for improvement. Identified business procedures are used as input for generation, and agents that automate specific operations are output. These intelligent agents mimic repetitive user actions using machine learning models, thereby improving operational efficiency. 【0295】 Step 7: 【0296】 The server sends the generated intelligent agent to the user's terminal. The agent's input includes an automation script, and its output allows the agent to be executed on the user's terminal. This allows the user to experience tasks automated by the agent, improving work efficiency. 【0297】 (Application Example 1) 【0298】 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." 【0299】 Improving the efficiency of work procedures is a crucial issue in modern industrial settings. However, many manual tasks are repetitive and inefficient. In particular, physical work procedures in factories are difficult to record on-site and rely on human visual judgment, resulting in insufficient data collection and analysis for efficiency improvements. Therefore, there is a need to improve the efficiency of work procedures using on-site visual information. 【0300】 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. 【0301】 In this invention, the server includes means for acquiring visual information from a user device, means for analyzing the acquired visual information and identifying work procedures, and means for visualizing the identified work procedures and generating current work procedures. This makes it possible to efficiently analyze and optimize work procedures using on-site visual information. 【0302】 A "user device" is a device operated by the user and is a terminal equipped with an interface for acquiring visual information. 【0303】 "Visual information" refers to image data and video data acquired by user devices, and is information used to record work procedures and operating methods. 【0304】 A "work procedure" is a sequence of operations and actions necessary to perform a specific task. 【0305】 "Visualization" refers to illustrating acquired work procedures and displaying them in an easy-to-understand format, thereby enabling intuitive understanding of business flows and procedures. 【0306】 The "AI role" is a role played by artificial intelligence generated for the purpose of improving the efficiency of work procedures and is a program for automatically executing specific tasks. 【0307】 "Transmission" means delivering the AI role to the user device and is the process of transmitting data using electronic means. 【0308】 The system for implementing this invention mainly consists of a user device and a server. 【0309】 The user device is a terminal equipped with a video acquisition function such as smart glasses and collects visual information of work procedures in the work environment. When the user performs work, the corresponding work procedures are recorded by the user device. The recorded visual information is uploaded from the user device to the server. 【0310】 The server provides a cloud environment for data analysis and analyzes the acquired visual information using machine learning frameworks such as Python and TensorFlow. In particular, it recognizes operation patterns and identifies work procedures, and visualizes the business process based on these. This visualized information serves as a basis for evaluating the potential for work efficiency improvement. The server has the ability to identify work that can be made more efficient based on the obtained information and generate appropriate AI roles. The AI role is designed to automate specific tasks and is transmitted to the user device. 【0311】 As a specific example, consider the case of optimizing a series of assembly procedures in line work. The video data recorded with smart glasses is analyzed by the server to visualize one work procedure. As a result of the analysis, it is identified that the screwing operation is being repeated as a candidate for automation, and automation by AI is proposed. The AI role is embodied as a control command for the screwing robot. 【0312】 An example of a prompt sentence for the generated AI model is "Analyze the assembly procedures in the factory from visual information and identify areas where automation is possible." 【0313】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0314】 Step 1: 【0315】 The user puts on smart glasses and begins working. Video data of the work procedure is recorded in real time on the device. Visual information is recorded as input data during this process. 【0316】 Step 2: 【0317】 The device uploads recorded visual information to a server via the internet. The visual information data becomes input to the server. At this point, the data is converted to an appropriate format and becomes ready for analysis on the server side. 【0318】 Step 3: 【0319】 The server analyzes the received visual information data. Using Python and TensorFlow, it performs pattern recognition on actions within the video and data calculations to identify work procedures. This identifies the dynamic flow and repetitive actions of the work, and outputs structured procedure data. 【0320】 Step 4: 【0321】 The server visualizes the identified work procedures. A visualized workflow is generated, preparing data to evaluate potential for efficiency improvements. This output is provided as a visualized flowchart or graph. 【0322】 Step 5: 【0323】 The server determines which tasks can be made more efficient based on the visualized information. Repetitive actions and simple tasks are identified as candidates for automation. This step provides a list of tasks that can be optimized and their details as output. 【0324】 Step 6: 【0325】 The server generates an AI role using a generated AI model based on the identified tasks. The AI ​​role is created as a set of instructions or scripts to execute the corresponding automation task, utilizing prompts appropriate to the current input data. The generated AI role is intended to execute specific automation steps. 【0326】 Step 7: 【0327】 The generated AI role is sent back to the terminal. The user's device receives this AI role and uses it to automate the actual work. The user receives support for the automated work provided by the AI ​​role, improving work efficiency. 【0328】 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. 【0329】 To implement this invention, a system integrating a dedicated recording application and an emotion engine is installed on the user terminal. When the user starts work, the recording application is launched and the PC screen recording begins. This records the user's operations and activities on the PC in real time. 【0330】 The terminal uploads the recorded data to the server. The server uses machine learning algorithms to analyze the recorded data and extract business procedures. Based on the analysis results, it performs process mapping and generates the current business flow. Furthermore, the server analyzes this business flow and considers possibilities for efficiency improvements. 【0331】 Furthermore, an emotion engine built into the user terminal analyzes the user's facial expressions, voice, and operation patterns to acquire emotional information. The emotion engine recognizes the user's emotional state and can measure, for example, stress levels and concentration levels. This makes it possible to monitor how the user's emotions change within the workflow. 【0332】 The server can adjust workflows based on data from the emotion engine. For example, if it detects that a user is experiencing stress, it will provide suggestions for optimizing their work accordingly. This allows users to perform their tasks more comfortably. 【0333】 Furthermore, AI agents are automatically generated based on optimized workflows and distributed to user terminals. These AI agents automatically perform repetitive tasks that users would normally do, reducing their workload. 【0334】 As a concrete example, consider data entry tasks. In a scenario where a user uses multiple spreadsheet programs to input standardized data, the emotion engine detects fatigue from the user's facial expressions. Based on this information, the server identifies parts of the workflow that can be made more efficient, and the AI ​​agent automates part of the data entry, thereby reducing the user's burden. 【0335】 This system provides an advanced method for simultaneously improving operational efficiency and enhancing the user's work experience. 【0336】 The following describes the processing flow. 【0337】 Step 1: 【0338】 Before the user begins work, the recording application on the terminal is launched and screen recording begins. Simultaneously, an emotion engine starts operating to monitor the user's facial expressions and voice. 【0339】 Step 2: 【0340】 The device records the user's PC screen and emotional data in real time. The recorded data includes detailed operations such as mouse movements, keyboard input, and application switching. The emotional engine uses the camera and microphone to continuously analyze the user's facial movements and voice tone. 【0341】 Step 3: 【0342】 After work hours, the terminal uploads video recordings and emotion data to the server. This allows the server to centrally receive both datasets. 【0343】 Step 4: 【0344】 The server analyzes the uploaded data. For recorded video data, machine learning techniques are used to extract and systematize work procedures. Emotional data is also analyzed to understand the user's emotional state at each step of the work process. 【0345】 Step 5: 【0346】 The server visualizes the workflow and maps the current workflow (As-Is) along with changes in the user's emotional state. This allows for understanding emotional fluctuations at each step. 【0347】 Step 6: 【0348】 The server analyzes the workflow and simultaneously evaluates areas for improvement and user stress. For example, it identifies steps where users are losing focus and suggests ways to streamline those steps. 【0349】 Step 7: 【0350】 Based on efficiency suggestions, the server redesigns business procedures and generates an optimized workflow (To-Be). The redesigned procedures also take into account improvements to the user's emotional state. 【0351】 Step 8: 【0352】 The server automatically generates AI agents based on optimized workflows. Before distributing the generated agents to users, simulation tests are performed to ensure they function correctly. 【0353】 Step 9: 【0354】 The generated AI agent is distributed to the user's terminal and applied to subsequent tasks. The AI ​​agent mimics the user's procedures to perform automation, reducing the user's workload. 【0355】 (Example 2) 【0356】 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". 【0357】 While streamlining user procedures in business operations is crucial, traditional methods only partially optimize workflows and fail to consider user emotional burden and psychological stress. Furthermore, generating and distributing automated agents that reflect streamlined workflows presents challenges. Addressing these issues is essential. 【0358】 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. 【0359】 In this invention, the server includes means for acquiring display information from a user terminal, means for analyzing the acquired display information and identifying business procedures, and means for analyzing the user's emotional state and using the emotional information to optimize the flow of activities. This simultaneously achieves increased efficiency in the business flow and reduced emotional burden on the user, and further enables the generation and distribution of automated agents based on the more efficient flow. 【0360】 A "user terminal" is a computer device used by a user, capable of displaying and manipulating data. 【0361】 "Displayed information" refers to digital data displayed on the screen of a user's terminal, and includes some of the information necessary for business operations. 【0362】 A "business procedure" is a sequence of operations and steps that must be followed to perform a specific task. 【0363】 An "activity flow" is a visual representation of business procedures, a diagrammatic representation that shows the structure of the current business process. 【0364】 An "intelligent agent" is a software program created to automate business processes and has the ability to automatically perform repetitive tasks. 【0365】 "Emotional information" refers to data that indicates a user's emotional state, and is psychological information extracted from facial expressions and voice. 【0366】 This invention provides a system that improves work efficiency while reducing the emotional burden on users operating user terminals. The main components of the system are a recording application installed on the user terminal, an emotion analysis engine, and a server for processing this data. 【0367】 User: 【0368】 When a user begins work, they launch a recording application on their terminal. This recording application captures the information displayed on the user's PC screen and collects digital data, including the terminal's operation status. This operation is performed using a standard PC or laptop. 【0369】 Terminal: 【0370】 The emotion analysis engine installed in the device captures facial expressions and voice in real time using the user's video camera and microphone, and extracts the user's emotional information. This allows for the evaluation of stress levels and concentration levels during actual work. The device also uploads the recorded video and emotional data to a server at predetermined intervals. 【0371】 server: 【0372】 The server first analyzes the business procedures using the uploaded data. Next, it generates a current business flow based on the analysis results and visualizes that flow in detail. The server then identifies parts of the business flow that can be made more efficient and proposes ways to optimize the activity flow while taking into account user sentiment information. After optimization is complete, the server automatically generates an intelligent agent and distributes it to the user's terminal. This agent reduces the user's workload by automatically performing repetitive tasks. 【0373】 Specific example: 【0374】 As a concrete example, consider a scenario where a user spends more than three hours using multiple spreadsheet programs for data entry. In this case, we propose a method where an emotion analysis engine detects fatigue from the user's facial expressions, and a server automates part of the task using an intelligent agent to reduce the burden. 【0375】 Example of a prompt: 【0376】 "How can we monitor users' emotional changes during work, analyze their stress levels, and optimize workflows?" 【0377】 This invention makes it possible to improve both operational efficiency and user satisfaction simultaneously. 【0378】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0379】 Step 1: 【0380】 The user launches a recording application on their device. The input is the information displayed on the user's PC screen. The recording application uses this input to capture digital data of the screen in real time. As a result, the device outputs the user's actions and display status as a video file. 【0381】 Step 2: 【0382】 The device uses an emotion analysis engine to capture the user's facial expressions and voice. The input consists of the user's video and audio data. Based on this, the emotion analysis engine extracts the user's emotional information and outputs stress levels and concentration levels as numerical data. 【0383】 Step 3: 【0384】 The device uploads recorded video data and emotion information to the server. The input consists of recorded video data and emotion information. The device sends the data to the server using a secure protocol and outputs a notification when the upload is complete. 【0385】 Step 4: 【0386】 The server analyzes the received video data. The input is video data of the screen display. The server uses a machine learning algorithm to identify business procedures and perform process mapping. The output is a list of identified business procedures and their visualization information. 【0387】 Step 5: 【0388】 The server optimizes business workflows based on received emotional information. Its inputs include emotional information and business procedures. The server generates efficiency suggestions based on the emotional state and designs an optimized workflow. The output consists of the optimization suggestions and the improved workflow. 【0389】 Step 6: 【0390】 The server automatically generates intelligent agents based on optimized business workflows. The input is an optimized business workflow. The server utilizes an AI model to develop agents for business automation and outputs agent files. 【0391】 Step 7: 【0392】 The server distributes the generated intelligent agent to the user terminal. The input is the agent file. The server completes the distribution process and receives output notifying the user that the agent is ready to use. 【0393】 (Application Example 2) 【0394】 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." 【0395】 This invention aims to solve the problem of providing a system that simultaneously improves operational efficiency and manages the emotional state of workers in production sites. In particular, there is a need for operational efficiency improvements that take into account the emotional state of workers, which has not been fully captured by conventional methods for optimizing workflows. 【0396】 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. 【0397】 In this invention, the server includes means for acquiring information from a user terminal, means for monitoring the emotional state of an employee using emotion analysis means, and means for adjusting the workflow based on emotional information. This makes it possible to optimize the workflow while taking into account the emotional state of the employee. 【0398】 A "user terminal" is an electronic device used by a user to retrieve or display information. 【0399】 "Means of acquiring information" refers to methods and devices for collecting necessary data from user terminals. 【0400】 "Means for identifying business procedures" refers to methods or devices for identifying specific business procedures based on acquired information. 【0401】 "Means for generating business process flows" refers to methods or devices for visually creating a business process flow based on identified business procedures. 【0402】 "Means for identifying areas for efficiency improvement" refer to methods and devices for analyzing business workflows and finding areas that can be improved. 【0403】 "Means for designing optimized business workflows" refers to methods or devices for restructuring business workflows based on identified areas for improvement. 【0404】 "Means for automatically generating AI agents" refers to methods or devices for automatically creating artificial intelligence agents according to an optimized workflow. 【0405】 "Means for distributing generated AI agents" refers to methods or devices for sending and installing the created AI agents on user terminals. 【0406】 "Emotional analysis means" refers to methods and devices for extracting and analyzing emotional information from a worker's facial expressions and actions. 【0407】 "Means for adjusting business processes based on emotional information" refers to methods or devices for changing the flow of business processes to an optimal state based on acquired emotional information. 【0408】 To implement this invention, a system is first required to acquire information from a user terminal. This system records user operations and sends the data to a server. The server has a high-performance processor and implements machine learning algorithms for data analysis. Machine learning frameworks such as TensorFlow or PyTorch can be used for this analysis. This allows for the identification of business procedures, and this information is used to visually generate a business flow. 【0409】 Next, in order to use emotion analysis, the user terminal needs to be equipped with a camera and sensors capable of facial recognition and motion analysis. OpenCV and Affectiva technologies can be used for this. The server uses this emotion data to collect emotional information and use it to redesign the workflow. 【0410】 Furthermore, on the server, areas for efficiency improvements are identified, and optimized workflows are designed. Based on this design, an AI agent is automatically generated. This AI agent is then immediately distributed to user terminals and automatically executes the necessary business procedures. 【0411】 As a concrete example of this embodiment, consider a process on a production line with a high defect rate. If the emotion analysis means detects a high stress level in the worker, it re-evaluates the workflow of that process and proposes reducing stress and lowering the defect rate by having the AI ​​agent automate some of the tasks. 【0412】 An example of a prompt message is, "In a factory production line, analyze the factors causing a decrease in work efficiency at a specific process, and generate improvement suggestions based on sentiment data." In this way, it becomes possible to improve both work efficiency and the morale of the workers. 【0413】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0414】 Step 1: 【0415】 The user terminal uses a camera and sensors to capture the worker's facial expressions and movements. This input data is converted into emotional information using a facial recognition algorithm. The output provides the worker's stress level and concentration level. 【0416】 Step 2: 【0417】 The user terminal records real-time operation data and work status, and sends this data to the server. Input data includes keystrokes, mouse movements, and screen display content. The server analyzes this data to identify work procedures and generates a workflow as output. 【0418】 Step 3: 【0419】 The server analyzes the generated business flow using a machine learning algorithm to identify areas for improvement to enhance efficiency. The input is the generated business flow, and the output is the identified areas for efficiency improvement. 【0420】 Step 4: 【0421】 The server designs new workflows and automatically generates AI agents based on the identified areas for improvement. This automated generation process utilizes a generative AI model. The input is information about areas for improvement, and the output is the automatically generated AI agent. 【0422】 Step 5: 【0423】 The server distributes and deploys the generated AI agents to user terminals. The AI ​​agents automatically execute the user's standard work procedures, reducing their workload. The output is the automated business process. 【0424】 Step 6: 【0425】 The server continuously receives feedback from the user terminal and optimizes the AI ​​agent's operation. The input is user feedback information, and the output is the improved AI agent. 【0426】 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. 【0427】 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. 【0428】 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. 【0429】 [Third Embodiment] 【0430】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0431】 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. 【0432】 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). 【0433】 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. 【0434】 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. 【0435】 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). 【0436】 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. 【0437】 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. 【0438】 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. 【0439】 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. 【0440】 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. 【0441】 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". 【0442】 To implement the present invention, a system comprising the following components is required. First, the user performs their daily tasks on a terminal with a dedicated application installed. When the user starts work, they launch an application with a recording function and record the PC screen. The recording captures the user's operations, application launch, visual information, etc., in chronological order. 【0443】 The terminal uploads the recorded data to the server. The server receives this recorded data and performs a detailed analysis using machine learning techniques. First, it recognizes patterns in the operations within the recorded data and extracts the business procedures. Next, the server analyzes these procedures and identifies details related to each step. Based on this data, it visualizes the current business flow. 【0444】 Once the workflow visualization is complete, the server analyzes the workflow and identifies areas where efficiency can be improved. For example, if it includes repetitive data entry or processing tasks, these are recognized as areas for improvement. Based on this information, the server redesigns the workflow for optimization and proposes improvements. 【0445】 The server automatically generates corresponding AI agents based on optimized workflows. These AI agents aim to mimic user procedures and automate specific operations. The generated AI agents are then distributed to user terminals. 【0446】 As a concrete example, consider data entry work. Assume a user is opening multiple spreadsheets and manually entering information. This process is recorded, and the server analyzes the screen capture data. If a series of steps related to data entry are identified and many repetitions are found within that process, the server proposes automating those repetitive tasks. An AI agent is then generated, allowing the agent to perform the data entry task on behalf of the user in the future. 【0447】 Thus, the system of the present invention provides a method for refining business processes and achieving a high level of efficiency by consistently performing everything from user business analysis to automation. 【0448】 The following describes the processing flow. 【0449】 Step 1: 【0450】 Before the user begins working on their PC, they launch a dedicated recording application and start recording the PC screen. This ensures that all operations performed during the work are recorded as video data. 【0451】 Step 2: 【0452】 When the device stops recording, the recorded data is automatically uploaded to the server. The data includes the user's operation history and details of the active window. 【0453】 Step 3: 【0454】 The server receives the recorded data and applies machine learning algorithms to analyze the work procedures. Specifically, it analyzes mouse click patterns and keyboard inputs to identify which actions belong to which work procedures. 【0455】 Step 4: 【0456】 The server visualizes the current business flow (As-Is) based on the analysis results. This allows users to visually confirm their own business processes. 【0457】 Step 5: 【0458】 The server further analyzes the workflow and identifies areas within the work process where efficiency can be improved. In particular, it focuses on repetitive and time-consuming steps. 【0459】 Step 6: 【0460】 The server designs an optimized workflow (To-Be) based on areas for improvement and generates improvement suggestions. These suggestions include eliminating unnecessary steps and automating processes. 【0461】 Step 7: 【0462】 The server automatically generates corresponding AI agents based on optimized workflows. These agents are designed with scripts to automatically process specific steps. 【0463】 Step 8: 【0464】 The generated AI agent is distributed to the user's device, and the environment for automating business processes is established. 【0465】 Step 9: 【0466】 The AI ​​agent mimics user actions and automatically executes specified work procedures, saving users time and effort. 【0467】 (Example 1) 【0468】 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." 【0469】 In today's work environment, many tasks involve cumbersome and repetitive procedures that hinder efficient work. Users face the challenge of having to spend a significant amount of time and effort manually. Furthermore, there are limits to manually streamlining existing processes, necessitating more sophisticated automation technologies. 【0470】 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. 【0471】 In this invention, the server includes means for acquiring recorded data from a user terminal, means for analyzing the acquired recorded data and identifying an operation procedure, means for visualizing the identified operation procedure and generating the current operation process, means for analyzing the operation process and identifying areas for improvement, means for automatically generating an intelligent agent based on the optimized operation process, and means for transmitting the generated intelligent agent to the user terminal. This enables automation to improve business efficiency. 【0472】 An "information processing device" is a computer system used to record user operations and is a device that collects and stores data. 【0473】 "Recorded data" refers to a collection of digital information that records user actions and changes on the screen in chronological order. 【0474】 "Operation procedure" refers to a series of user operations or processes performed to carry out a specific task. 【0475】 "Visualization" is the process of representing extracted operational steps in the form of flowcharts or process maps, making them intuitively understandable. 【0476】 "Operation process" refers to a visual representation of the steps and procedures involved in carrying out a task. 【0477】 "Room for improvement" refers to parts of the current business process that have the potential to reduce or improve repetitive or inefficient steps. 【0478】 An "intelligent agent" is a program that uses artificial intelligence technology to mimic user actions and automate specific work procedures. 【0479】 "User terminal" refers to a computer or other digital device used by a user to perform their duties. 【0480】 This invention is an automated system designed to improve user work efficiency. Users record their daily operations using a terminal with a dedicated application installed. The terminal transmits the recorded data to a server via the internet. This recorded data includes the user's manual actions and changes on the screen. 【0481】 The server receives this recorded data and analyzes it using a machine learning model. Specifically, it recognizes patterns in user operations within the data and extracts business procedures. The hardware used for this analysis is a server device capable of high-speed processing, and the software implements machine learning algorithms for pattern recognition and data analysis. 【0482】 Once the analysis is complete, the server visually represents the business procedures as flowcharts and process maps, generating a business flow. Next, the business flow is examined in detail to identify repetitive tasks and parts that can be automated. This leads to increased efficiency in business operations. 【0483】 The server automatically generates intelligent agents based on optimized workflows. These agents mimic the steps the user was performing and automatically execute specific operations. The generated agents are then distributed to the user's terminal. 【0484】 As a concrete example, consider a scenario where a user manually enters multiple data sets into different formats every day. By recording this process, the server analyzes the data entry steps and identifies repetitive operations. An intelligent agent is then generated, and in subsequent instances, this data entry can be automated by the agent, significantly reducing the user's time and effort. 【0485】 An example of a prompt to input into the generating AI model is: "Analyze the recorded PC screen data and extract the user's work procedures. Next, identify repetitive tasks and parts that can be automated, and design the optimal workflow." This prompt helps the system create efficient work processes based on the user's needs. 【0486】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0487】 Step 1: 【0488】 The user installs a dedicated application on their device and begins their daily work. At the start of their workday, the user activates the application's recording function to record their PC screen. In this process, work operation information is used as user input, and the output is recorded data. During recording, the user proceeds with their work as usual, so all operations during that time are recorded chronologically. 【0489】 Step 2: 【0490】 After recording is complete, the device uploads the recorded data to the server. During this process, the device transmits the data over the network, and the server receives it. The input is the recorded data, and the server can acquire this data as output. The upload process includes checking the approximate file size and communication speed, as well as a retransmission function in case of errors. 【0491】 Step 3: 【0492】 The server analyzes the acquired video data. First, it uses a machine learning algorithm to recognize patterns in user actions from the data. This analysis extracts business procedures. Video data is used as input, and patterned business procedures are generated as output. Specifically, it analyzes the frequency and order of clicks and input operations to identify standard procedures. 【0493】 Step 4: 【0494】 The server visualizes the extracted business procedures. This visualization represents the workflow as a flowchart or process map, making it intuitively understandable. The visualization requires business procedure data as input, and the output is a clear and easy-to-understand visual representation of the business processes. This allows users and administrators to efficiently grasp the current workflow. 【0495】 Step 5: 【0496】 The server analyzes areas for efficiency improvements based on the visualized workflow. If there are repetitive operations or time-consuming steps within the workflow, they are identified as targets for automation. The visualized workflow is used as input, and areas for improvement are identified as output. This allows for the discovery of potential areas for optimization. 【0497】 Step 6: 【0498】 The server automatically generates intelligent agents based on areas for improvement. Identified business procedures are used as input for generation, and agents that automate specific operations are output. These intelligent agents mimic repetitive user actions using machine learning models, thereby improving operational efficiency. 【0499】 Step 7: 【0500】 The server sends the generated intelligent agent to the user's terminal. The agent's input includes an automation script, and its output allows the agent to be executed on the user's terminal. This allows the user to experience tasks automated by the agent, improving work efficiency. 【0501】 (Application Example 1) 【0502】 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." 【0503】 Improving the efficiency of work procedures is a crucial issue in modern industrial settings. However, many manual tasks are repetitive and inefficient. In particular, physical work procedures in factories are difficult to record on-site and rely on human visual judgment, resulting in insufficient data collection and analysis for efficiency improvements. Therefore, there is a need to improve the efficiency of work procedures using on-site visual information. 【0504】 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. 【0505】 In this invention, the server includes means for acquiring visual information from a user device, means for analyzing the acquired visual information and identifying work procedures, and means for visualizing the identified work procedures and generating current work procedures. This makes it possible to efficiently analyze and optimize work procedures using on-site visual information. 【0506】 A "user device" is a device operated by the user and is a terminal equipped with an interface for acquiring visual information. 【0507】 "Visual information" refers to image data and video data acquired by user devices, and is information used to record work procedures and operating methods. 【0508】 A "work procedure" is a sequence of operations and actions necessary to perform a specific task. 【0509】 "Visualization" refers to illustrating acquired work procedures and displaying them in an easy-to-understand format, thereby enabling intuitive understanding of business flows and procedures. 【0510】 An "AI role" is a role created by artificial intelligence for the purpose of streamlining work procedures, and is a program designed to automatically perform specific tasks. 【0511】 "Transmission" refers to the process of delivering AI roles to user devices, and involves transmitting data using electronic means. 【0512】 The system for implementing this invention mainly consists of a user device and a server. 【0513】 The user device is a terminal equipped with video acquisition capabilities, similar to smart glasses, that collects visual information of work procedures in the work environment. When the user performs a task, the relevant work procedure is recorded by the user device. The recorded visual information is uploaded from the user device to the server. 【0514】 The server provides a cloud environment for data analysis, using machine learning frameworks such as Python and TensorFlow to analyze acquired visual information. Specifically, it recognizes behavioral patterns and identifies work procedures, visualizing workflows based on these findings. This visualized information forms the basis for evaluating the potential for work efficiency improvements. Based on the acquired information, the server has the capability to identify tasks that can be streamlined and generate appropriate AI roles. These AI roles are designed to automate specific tasks and are transmitted to user devices. 【0515】 As a concrete example, consider optimizing a series of assembly steps in a production line. Video data recorded by smart glasses is analyzed on a server to visualize a single work step. The analysis identifies screw tightening as a repetitive task and proposes automation using AI. The AI's role is then concretely defined as control commands for a screw-tightening robot. 【0516】 An example of a prompt for the generated AI model would be, "Analyze the factory assembly procedure from visual information and identify the parts that can be automated." 【0517】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0518】 Step 1: 【0519】 The user puts on smart glasses and begins working. Video data of the work procedure is recorded in real time on the device. Visual information is recorded as input data during this process. 【0520】 Step 2: 【0521】 The device uploads recorded visual information to a server via the internet. The visual information data becomes input to the server. At this point, the data is converted to an appropriate format and becomes ready for analysis on the server side. 【0522】 Step 3: 【0523】 The server analyzes the received visual information data. Using Python and TensorFlow, it performs pattern recognition on actions within the video and data calculations to identify work procedures. This identifies the dynamic flow and repetitive actions of the work, and outputs structured procedure data. 【0524】 Step 4: 【0525】 The server visualizes the identified work procedures. A visualized workflow is generated, preparing data to evaluate potential for efficiency improvements. This output is provided as a visualized flowchart or graph. 【0526】 Step 5: 【0527】 The server determines which tasks can be made more efficient based on the visualized information. Repetitive actions and simple tasks are identified as candidates for automation. This step provides a list of tasks that can be optimized and their details as output. 【0528】 Step 6: 【0529】 The server generates an AI role using a generated AI model based on the identified tasks. The AI ​​role is created as a set of instructions or scripts to execute the corresponding automation task, utilizing prompts appropriate to the current input data. The generated AI role is intended to execute specific automation steps. 【0530】 Step 7: 【0531】 The generated AI role is sent back to the terminal. The user's device receives this AI role and uses it to automate the actual work. The user receives support for the automated work provided by the AI ​​role, improving work efficiency. 【0532】 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. 【0533】 To implement this invention, a system integrating a dedicated recording application and an emotion engine is installed on the user terminal. When the user starts work, the recording application is launched and the PC screen recording begins. This records the user's operations and activities on the PC in real time. 【0534】 The terminal uploads the recorded data to the server. The server uses machine learning algorithms to analyze the recorded data and extract business procedures. Based on the analysis results, it performs process mapping and generates the current business flow. Furthermore, the server analyzes this business flow and considers possibilities for efficiency improvements. 【0535】 Furthermore, an emotion engine built into the user terminal analyzes the user's facial expressions, voice, and operation patterns to acquire emotional information. The emotion engine recognizes the user's emotional state and can measure, for example, stress levels and concentration levels. This makes it possible to monitor how the user's emotions change within the workflow. 【0536】 The server can adjust workflows based on data from the emotion engine. For example, if it detects that a user is experiencing stress, it will provide suggestions for optimizing their work accordingly. This allows users to perform their tasks more comfortably. 【0537】 Furthermore, AI agents are automatically generated based on optimized workflows and distributed to user terminals. These AI agents automatically perform repetitive tasks that users would normally do, reducing their workload. 【0538】 As a concrete example, consider data entry tasks. In a scenario where a user uses multiple spreadsheet programs to input standardized data, the emotion engine detects fatigue from the user's facial expressions. Based on this information, the server identifies parts of the workflow that can be made more efficient, and the AI ​​agent automates part of the data entry, thereby reducing the user's burden. 【0539】 This system provides an advanced method for simultaneously improving operational efficiency and enhancing the user's work experience. 【0540】 The following describes the processing flow. 【0541】 Step 1: 【0542】 Before the user begins work, the recording application on the terminal is launched and screen recording begins. Simultaneously, an emotion engine starts operating to monitor the user's facial expressions and voice. 【0543】 Step 2: 【0544】 The device records the user's PC screen and emotional data in real time. The recorded data includes detailed operations such as mouse movements, keyboard input, and application switching. The emotional engine uses the camera and microphone to continuously analyze the user's facial movements and voice tone. 【0545】 Step 3: 【0546】 After work hours, the terminal uploads video recordings and emotion data to the server. This allows the server to centrally receive both datasets. 【0547】 Step 4: 【0548】 The server analyzes the uploaded data. For recorded video data, machine learning techniques are used to extract and systematize work procedures. Emotional data is also analyzed to understand the user's emotional state at each step of the work process. 【0549】 Step 5: 【0550】 The server visualizes the workflow and maps the current workflow (As-Is) along with changes in the user's emotional state. This allows for understanding emotional fluctuations at each step. 【0551】 Step 6: 【0552】 The server analyzes the workflow and simultaneously evaluates areas for improvement and user stress. For example, it identifies steps where users are losing focus and suggests ways to streamline those steps. 【0553】 Step 7: 【0554】 Based on efficiency suggestions, the server redesigns business procedures and generates an optimized workflow (To-Be). The redesigned procedures also take into account improvements to the user's emotional state. 【0555】 Step 8: 【0556】 The server automatically generates AI agents based on optimized workflows. Before distributing the generated agents to users, simulation tests are performed to ensure they function correctly. 【0557】 Step 9: 【0558】 The generated AI agent is distributed to the user's terminal and applied to subsequent tasks. The AI ​​agent mimics the user's procedures to perform automation, reducing the user's workload. 【0559】 (Example 2) 【0560】 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." 【0561】 While streamlining user procedures in business operations is crucial, traditional methods only partially optimize workflows and fail to consider user emotional burden and psychological stress. Furthermore, generating and distributing automated agents that reflect streamlined workflows presents challenges. Addressing these issues is essential. 【0562】 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. 【0563】 In this invention, the server includes means for acquiring display information from a user terminal, means for analyzing the acquired display information and identifying business procedures, and means for analyzing the user's emotional state and using the emotional information to optimize the flow of activities. This simultaneously achieves increased efficiency in the business flow and reduced emotional burden on the user, and further enables the generation and distribution of automated agents based on the more efficient flow. 【0564】 A "user terminal" is a computer device used by a user, capable of displaying and manipulating data. 【0565】 "Displayed information" refers to digital data displayed on the screen of a user's terminal, and includes some of the information necessary for business operations. 【0566】 A "business procedure" is a sequence of operations and steps that must be followed to perform a specific task. 【0567】 An "activity flow" is a visual representation of business procedures, a diagrammatic representation that shows the structure of the current business process. 【0568】 An "intelligent agent" is a software program created to automate business processes and has the ability to automatically perform repetitive tasks. 【0569】 "Emotional information" refers to data that indicates a user's emotional state, and is psychological information extracted from facial expressions and voice. 【0570】 This invention provides a system that improves work efficiency while reducing the emotional burden on users operating user terminals. The main components of the system are a recording application installed on the user terminal, an emotion analysis engine, and a server for processing this data. 【0571】 User: 【0572】 When a user begins work, they launch a recording application on their terminal. This recording application captures the information displayed on the user's PC screen and collects digital data, including the terminal's operation status. This operation is performed using a standard PC or laptop. 【0573】 Terminal: 【0574】 The emotion analysis engine installed in the device captures facial expressions and voice in real time using the user's video camera and microphone, and extracts the user's emotional information. This allows for the evaluation of stress levels and concentration levels during actual work. The device also uploads the recorded video and emotional data to a server at predetermined intervals. 【0575】 server: 【0576】 The server first analyzes the business procedures using the uploaded data. Next, it generates a current business flow based on the analysis results and visualizes that flow in detail. The server then identifies parts of the business flow that can be made more efficient and proposes ways to optimize the activity flow while taking into account user sentiment information. After optimization is complete, the server automatically generates an intelligent agent and distributes it to the user's terminal. This agent reduces the user's workload by automatically performing repetitive tasks. 【0577】 Specific example: 【0578】 As a concrete example, consider a scenario where a user spends more than three hours using multiple spreadsheet programs for data entry. In this case, we propose a method where an emotion analysis engine detects fatigue from the user's facial expressions, and a server automates part of the task using an intelligent agent to reduce the burden. 【0579】 Example of a prompt: 【0580】 "How can we monitor users' emotional changes during work, analyze their stress levels, and optimize workflows?" 【0581】 This invention makes it possible to improve both operational efficiency and user satisfaction simultaneously. 【0582】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0583】 Step 1: 【0584】 The user launches a recording application on their device. The input is the information displayed on the user's PC screen. The recording application uses this input to capture digital data of the screen in real time. As a result, the device outputs the user's actions and display status as a video file. 【0585】 Step 2: 【0586】 The device uses an emotion analysis engine to capture the user's facial expressions and voice. The input consists of the user's video and audio data. Based on this, the emotion analysis engine extracts the user's emotional information and outputs stress levels and concentration levels as numerical data. 【0587】 Step 3: 【0588】 The device uploads recorded video data and emotion information to the server. The input consists of recorded video data and emotion information. The device sends the data to the server using a secure protocol and outputs a notification when the upload is complete. 【0589】 Step 4: 【0590】 The server analyzes the received video data. The input is video data of the screen display. The server uses a machine learning algorithm to identify business procedures and perform process mapping. The output is a list of identified business procedures and their visualization information. 【0591】 Step 5: 【0592】 The server optimizes business workflows based on received emotional information. Its inputs include emotional information and business procedures. The server generates efficiency suggestions based on the emotional state and designs an optimized workflow. The output consists of the optimization suggestions and the improved workflow. 【0593】 Step 6: 【0594】 The server automatically generates intelligent agents based on optimized business workflows. The input is an optimized business workflow. The server utilizes an AI model to develop agents for business automation and outputs agent files. 【0595】 Step 7: 【0596】 The server distributes the generated intelligent agent to the user terminal. The input is the agent file. The server completes the distribution process and receives output notifying the user that the agent is ready to use. 【0597】 (Application Example 2) 【0598】 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." 【0599】 This invention aims to solve the problem of providing a system that simultaneously improves operational efficiency and manages the emotional state of workers in production sites. In particular, there is a need for operational efficiency improvements that take into account the emotional state of workers, which has not been fully captured by conventional methods for optimizing workflows. 【0600】 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. 【0601】 In this invention, the server includes means for acquiring information from a user terminal, means for monitoring the emotional state of an employee using emotion analysis means, and means for adjusting the workflow based on emotional information. This makes it possible to optimize the workflow while taking into account the emotional state of the employee. 【0602】 A "user terminal" is an electronic device used by a user to retrieve or display information. 【0603】 "Means of acquiring information" refers to methods and devices for collecting necessary data from user terminals. 【0604】 "Means for identifying business procedures" refers to methods or devices for identifying specific business procedures based on acquired information. 【0605】 "Means for generating business process flows" refers to methods or devices for visually creating a business process flow based on identified business procedures. 【0606】 "Means for identifying areas for efficiency improvement" refer to methods and devices for analyzing business workflows and finding areas that can be improved. 【0607】 "Means for designing optimized business workflows" refers to methods or devices for restructuring business workflows based on identified areas for improvement. 【0608】 "Means for automatically generating AI agents" refers to methods or devices for automatically creating artificial intelligence agents according to an optimized workflow. 【0609】 "Means for distributing generated AI agents" refers to methods or devices for sending and installing the created AI agents on user terminals. 【0610】 "Emotional analysis means" refers to methods and devices for extracting and analyzing emotional information from a worker's facial expressions and actions. 【0611】 "Means for adjusting business processes based on emotional information" refers to methods or devices for changing the flow of business processes to an optimal state based on acquired emotional information. 【0612】 To implement this invention, a system is first required to acquire information from a user terminal. This system records user operations and sends the data to a server. The server has a high-performance processor and implements machine learning algorithms for data analysis. Machine learning frameworks such as TensorFlow or PyTorch can be used for this analysis. This allows for the identification of business procedures, and this information is used to visually generate a business flow. 【0613】 Next, in order to use emotion analysis, the user terminal needs to be equipped with a camera and sensors capable of facial recognition and motion analysis. OpenCV and Affectiva technologies can be used for this. The server uses this emotion data to collect emotional information and use it to redesign the workflow. 【0614】 Furthermore, on the server, areas for efficiency improvements are identified, and optimized workflows are designed. Based on this design, an AI agent is automatically generated. This AI agent is then immediately distributed to user terminals and automatically executes the necessary business procedures. 【0615】 As a concrete example of this embodiment, consider a process on a production line with a high defect rate. If the emotion analysis means detects a high stress level in the worker, it re-evaluates the workflow of that process and proposes reducing stress and lowering the defect rate by having the AI ​​agent automate some of the tasks. 【0616】 An example of a prompt message is, "In a factory production line, analyze the factors causing a decrease in work efficiency at a specific process, and generate improvement suggestions based on sentiment data." In this way, it becomes possible to improve both work efficiency and the morale of the workers. 【0617】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0618】 Step 1: 【0619】 The user terminal uses a camera and sensors to capture the worker's facial expressions and movements. This input data is converted into emotional information using a facial recognition algorithm. The output provides the worker's stress level and concentration level. 【0620】 Step 2: 【0621】 The user terminal records real-time operation data and work status, and sends this data to the server. Input data includes keystrokes, mouse movements, and screen display content. The server analyzes this data to identify work procedures and generates a workflow as output. 【0622】 Step 3: 【0623】 The server analyzes the generated business flow using a machine learning algorithm to identify areas for improvement to enhance efficiency. The input is the generated business flow, and the output is the identified areas for efficiency improvement. 【0624】 Step 4: 【0625】 The server designs new workflows and automatically generates AI agents based on the identified areas for improvement. This automated generation process utilizes a generative AI model. The input is information about areas for improvement, and the output is the automatically generated AI agent. 【0626】 Step 5: 【0627】 The server distributes and deploys the generated AI agents to user terminals. The AI ​​agents automatically execute the user's standard work procedures, reducing their workload. The output is the automated business process. 【0628】 Step 6: 【0629】 The server continuously receives feedback from the user terminal and optimizes the AI ​​agent's operation. The input is user feedback information, and the output is the improved AI agent. 【0630】 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. 【0631】 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. 【0632】 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. 【0633】 [Fourth Embodiment] 【0634】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0635】 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. 【0636】 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). 【0637】 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. 【0638】 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. 【0639】 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). 【0640】 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. 【0641】 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. 【0642】 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. 【0643】 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. 【0644】 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. 【0645】 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. 【0646】 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". 【0647】 To implement the present invention, a system comprising the following components is required. First, the user performs their daily tasks on a terminal with a dedicated application installed. When the user starts work, they launch an application with a recording function and record the PC screen. The recording captures the user's operations, application launch, visual information, etc., in chronological order. 【0648】 The terminal uploads the recorded data to the server. The server receives this recorded data and performs a detailed analysis using machine learning techniques. First, it recognizes patterns in the operations within the recorded data and extracts the business procedures. Next, the server analyzes these procedures and identifies details related to each step. Based on this data, it visualizes the current business flow. 【0649】 Once the workflow visualization is complete, the server analyzes the workflow and identifies areas where efficiency can be improved. For example, if it includes repetitive data entry or processing tasks, these are recognized as areas for improvement. Based on this information, the server redesigns the workflow for optimization and proposes improvements. 【0650】 The server automatically generates corresponding AI agents based on optimized workflows. These AI agents aim to mimic user procedures and automate specific operations. The generated AI agents are then distributed to user terminals. 【0651】 As a concrete example, consider data entry work. Assume a user is opening multiple spreadsheets and manually entering information. This process is recorded, and the server analyzes the screen capture data. If a series of steps related to data entry are identified and many repetitions are found within that process, the server proposes automating those repetitive tasks. An AI agent is then generated, allowing the agent to perform the data entry task on behalf of the user in the future. 【0652】 Thus, the system of the present invention provides a method for refining business processes and achieving a high level of efficiency by consistently performing everything from user business analysis to automation. 【0653】 The following describes the processing flow. 【0654】 Step 1: 【0655】 Before the user begins working on their PC, they launch a dedicated recording application and start recording the PC screen. This ensures that all operations performed during the work are recorded as video data. 【0656】 Step 2: 【0657】 When the device stops recording, the recorded data is automatically uploaded to the server. The data includes the user's operation history and details of the active window. 【0658】 Step 3: 【0659】 The server receives the recorded data and applies machine learning algorithms to analyze the work procedures. Specifically, it analyzes mouse click patterns and keyboard inputs to identify which actions belong to which work procedures. 【0660】 Step 4: 【0661】 The server visualizes the current business flow (As-Is) based on the analysis results. This allows users to visually confirm their own business processes. 【0662】 Step 5: 【0663】 The server further analyzes the workflow and identifies areas within the work process where efficiency can be improved. In particular, it focuses on repetitive and time-consuming steps. 【0664】 Step 6: 【0665】 The server designs an optimized workflow (To-Be) based on areas for improvement and generates improvement suggestions. These suggestions include eliminating unnecessary steps and automating processes. 【0666】 Step 7: 【0667】 The server automatically generates corresponding AI agents based on optimized workflows. These agents are designed with scripts to automatically process specific steps. 【0668】 Step 8: 【0669】 The generated AI agent is distributed to the user's device, and the environment for automating business processes is established. 【0670】 Step 9: 【0671】 The AI ​​agent mimics user actions and automatically executes specified work procedures, saving users time and effort. 【0672】 (Example 1) 【0673】 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". 【0674】 In today's work environment, many tasks involve cumbersome and repetitive procedures that hinder efficient work. Users face the challenge of having to spend a significant amount of time and effort manually. Furthermore, there are limits to manually streamlining existing processes, necessitating more sophisticated automation technologies. 【0675】 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. 【0676】 In this invention, the server includes means for acquiring recorded data from a user terminal, means for analyzing the acquired recorded data and identifying an operation procedure, means for visualizing the identified operation procedure and generating the current operation process, means for analyzing the operation process and identifying areas for improvement, means for automatically generating an intelligent agent based on the optimized operation process, and means for transmitting the generated intelligent agent to the user terminal. This enables automation to improve business efficiency. 【0677】 An "information processing device" is a computer system used to record user operations and is a device that collects and stores data. 【0678】 "Recorded data" refers to a collection of digital information that records user actions and changes on the screen in chronological order. 【0679】 "Operation procedure" refers to a series of user operations or processes performed to carry out a specific task. 【0680】 "Visualization" is the process of representing extracted operational steps in the form of flowcharts or process maps, making them intuitively understandable. 【0681】 "Operation process" refers to a visual representation of the steps and procedures involved in carrying out a task. 【0682】 "Room for improvement" refers to parts of the current business process that have the potential to reduce or improve repetitive or inefficient steps. 【0683】 An "intelligent agent" is a program that uses artificial intelligence technology to mimic user actions and automate specific work procedures. 【0684】 "User terminal" refers to a computer or other digital device used by a user to perform their duties. 【0685】 This invention is an automated system designed to improve user work efficiency. Users record their daily operations using a terminal with a dedicated application installed. The terminal transmits the recorded data to a server via the internet. This recorded data includes the user's manual actions and changes on the screen. 【0686】 The server receives this recorded data and analyzes it using a machine learning model. Specifically, it recognizes patterns in user operations within the data and extracts business procedures. The hardware used for this analysis is a server device capable of high-speed processing, and the software implements machine learning algorithms for pattern recognition and data analysis. 【0687】 Once the analysis is complete, the server visually represents the business procedures as flowcharts and process maps, generating a business flow. Next, the business flow is examined in detail to identify repetitive tasks and parts that can be automated. This leads to increased efficiency in business operations. 【0688】 The server automatically generates intelligent agents based on optimized workflows. These agents mimic the steps the user was performing and automatically execute specific operations. The generated agents are then distributed to the user's terminal. 【0689】 As a concrete example, consider a scenario where a user manually enters multiple data sets into different formats every day. By recording this process, the server analyzes the data entry steps and identifies repetitive operations. An intelligent agent is then generated, and in subsequent instances, this data entry can be automated by the agent, significantly reducing the user's time and effort. 【0690】 An example of a prompt to input into the generating AI model is: "Analyze the recorded PC screen data and extract the user's work procedures. Next, identify repetitive tasks and parts that can be automated, and design the optimal workflow." This prompt helps the system create efficient work processes based on the user's needs. 【0691】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0692】 Step 1: 【0693】 The user installs a dedicated application on their device and begins their daily work. At the start of their workday, the user activates the application's recording function to record their PC screen. In this process, work operation information is used as user input, and the output is recorded data. During recording, the user proceeds with their work as usual, so all operations during that time are recorded chronologically. 【0694】 Step 2: 【0695】 After recording is complete, the device uploads the recorded data to the server. During this process, the device transmits the data over the network, and the server receives it. The input is the recorded data, and the server can acquire this data as output. The upload process includes checking the approximate file size and communication speed, as well as a retransmission function in case of errors. 【0696】 Step 3: 【0697】 The server analyzes the acquired video data. First, it uses a machine learning algorithm to recognize patterns in user actions from the data. This analysis extracts business procedures. Video data is used as input, and patterned business procedures are generated as output. Specifically, it analyzes the frequency and order of clicks and input operations to identify standard procedures. 【0698】 Step 4: 【0699】 The server visualizes the extracted business procedures. This visualization represents the workflow as a flowchart or process map, making it intuitively understandable. The visualization requires business procedure data as input, and the output is a clear and easy-to-understand visual representation of the business processes. This allows users and administrators to efficiently grasp the current workflow. 【0700】 Step 5: 【0701】 The server analyzes areas for efficiency improvements based on the visualized workflow. If there are repetitive operations or time-consuming steps within the workflow, they are identified as targets for automation. The visualized workflow is used as input, and areas for improvement are identified as output. This allows for the discovery of potential areas for optimization. 【0702】 Step 6: 【0703】 The server automatically generates intelligent agents based on areas for improvement. Identified business procedures are used as input for generation, and agents that automate specific operations are output. These intelligent agents mimic repetitive user actions using machine learning models, thereby improving operational efficiency. 【0704】 Step 7: 【0705】 The server sends the generated intelligent agent to the user's terminal. The agent's input includes an automation script, and its output allows the agent to be executed on the user's terminal. This allows the user to experience tasks automated by the agent, improving work efficiency. 【0706】 (Application Example 1) 【0707】 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". 【0708】 Improving the efficiency of work procedures is a crucial issue in modern industrial settings. However, many manual tasks are repetitive and inefficient. In particular, physical work procedures in factories are difficult to record on-site and rely on human visual judgment, resulting in insufficient data collection and analysis for efficiency improvements. Therefore, there is a need to improve the efficiency of work procedures using on-site visual information. 【0709】 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. 【0710】 In this invention, the server includes means for acquiring visual information from a user device, means for analyzing the acquired visual information and identifying work procedures, and means for visualizing the identified work procedures and generating current work procedures. This makes it possible to efficiently analyze and optimize work procedures using on-site visual information. 【0711】 A "user device" is a device operated by the user and is a terminal equipped with an interface for acquiring visual information. 【0712】 "Visual information" refers to image data and video data acquired by user devices, and is information used to record work procedures and operating methods. 【0713】 A "work procedure" is a sequence of operations and actions necessary to perform a specific task. 【0714】 "Visualization" refers to illustrating acquired work procedures and displaying them in an easy-to-understand format, thereby enabling intuitive understanding of business flows and procedures. 【0715】 An "AI role" is a role created by artificial intelligence for the purpose of streamlining work procedures, and is a program designed to automatically perform specific tasks. 【0716】 "Transmission" refers to the process of delivering AI roles to user devices, and involves transmitting data using electronic means. 【0717】 The system for implementing this invention mainly consists of a user device and a server. 【0718】 The user device is a terminal equipped with video acquisition capabilities, similar to smart glasses, that collects visual information of work procedures in the work environment. When the user performs a task, the relevant work procedure is recorded by the user device. The recorded visual information is uploaded from the user device to the server. 【0719】 The server provides a cloud environment for data analysis, using machine learning frameworks such as Python and TensorFlow to analyze acquired visual information. Specifically, it recognizes behavioral patterns and identifies work procedures, visualizing workflows based on these findings. This visualized information forms the basis for evaluating the potential for work efficiency improvements. Based on the acquired information, the server has the capability to identify tasks that can be streamlined and generate appropriate AI roles. These AI roles are designed to automate specific tasks and are transmitted to user devices. 【0720】 As a concrete example, consider optimizing a series of assembly steps in a production line. Video data recorded by smart glasses is analyzed on a server to visualize a single work step. The analysis identifies screw tightening as a repetitive task and proposes automation using AI. The AI's role is then concretely defined as control commands for a screw-tightening robot. 【0721】 An example of a prompt for the generated AI model would be, "Analyze the factory assembly procedure from visual information and identify the parts that can be automated." 【0722】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0723】 Step 1: 【0724】 The user puts on smart glasses and begins working. Video data of the work procedure is recorded in real time on the device. Visual information is recorded as input data during this process. 【0725】 Step 2: 【0726】 The device uploads recorded visual information to a server via the internet. The visual information data becomes input to the server. At this point, the data is converted to an appropriate format and becomes ready for analysis on the server side. 【0727】 Step 3: 【0728】 The server analyzes the received visual information data. Using Python and TensorFlow, it performs pattern recognition on actions within the video and data calculations to identify work procedures. This identifies the dynamic flow and repetitive actions of the work, and outputs structured procedure data. 【0729】 Step 4: 【0730】 The server visualizes the identified work procedures. A visualized workflow is generated, preparing data to evaluate potential for efficiency improvements. This output is provided as a visualized flowchart or graph. 【0731】 Step 5: 【0732】 The server determines which tasks can be made more efficient based on the visualized information. Repetitive actions and simple tasks are identified as candidates for automation. This step provides a list of tasks that can be optimized and their details as output. 【0733】 Step 6: 【0734】 The server generates an AI role using a generated AI model based on the identified tasks. The AI ​​role is created as a set of instructions or scripts to execute the corresponding automation task, utilizing prompts appropriate to the current input data. The generated AI role is intended to execute specific automation steps. 【0735】 Step 7: 【0736】 The generated AI role is sent back to the terminal. The user's device receives this AI role and uses it to automate the actual work. The user receives support for the automated work provided by the AI ​​role, improving work efficiency. 【0737】 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. 【0738】 To implement this invention, a system integrating a dedicated recording application and an emotion engine is installed on the user terminal. When the user starts work, the recording application is launched and the PC screen recording begins. This records the user's operations and activities on the PC in real time. 【0739】 The terminal uploads the recorded data to the server. The server uses machine learning algorithms to analyze the recorded data and extract business procedures. Based on the analysis results, it performs process mapping and generates the current business flow. Furthermore, the server analyzes this business flow and considers possibilities for efficiency improvements. 【0740】 Furthermore, an emotion engine built into the user terminal analyzes the user's facial expressions, voice, and operation patterns to acquire emotional information. The emotion engine recognizes the user's emotional state and can measure, for example, stress levels and concentration levels. This makes it possible to monitor how the user's emotions change within the workflow. 【0741】 The server can adjust workflows based on data from the emotion engine. For example, if it detects that a user is experiencing stress, it will provide suggestions for optimizing their work accordingly. This allows users to perform their tasks more comfortably. 【0742】 Furthermore, AI agents are automatically generated based on optimized workflows and distributed to user terminals. These AI agents automatically perform repetitive tasks that users would normally do, reducing their workload. 【0743】 As a concrete example, consider data entry tasks. In a scenario where a user uses multiple spreadsheet programs to input standardized data, the emotion engine detects fatigue from the user's facial expressions. Based on this information, the server identifies parts of the workflow that can be made more efficient, and the AI ​​agent automates part of the data entry, thereby reducing the user's burden. 【0744】 This system provides an advanced method for simultaneously improving operational efficiency and enhancing the user's work experience. 【0745】 The following describes the processing flow. 【0746】 Step 1: 【0747】 Before the user begins work, the recording application on the terminal is launched and screen recording begins. Simultaneously, an emotion engine starts operating to monitor the user's facial expressions and voice. 【0748】 Step 2: 【0749】 The device records the user's PC screen and emotional data in real time. The recorded data includes detailed operations such as mouse movements, keyboard input, and application switching. The emotional engine uses the camera and microphone to continuously analyze the user's facial movements and voice tone. 【0750】 Step 3: 【0751】 After work hours, the terminal uploads video recordings and emotion data to the server. This allows the server to centrally receive both datasets. 【0752】 Step 4: 【0753】 The server analyzes the uploaded data. For recorded video data, machine learning techniques are used to extract and systematize work procedures. Emotional data is also analyzed to understand the user's emotional state at each step of the work process. 【0754】 Step 5: 【0755】 The server visualizes the workflow and maps the current workflow (As-Is) along with changes in the user's emotional state. This allows for understanding emotional fluctuations at each step. 【0756】 Step 6: 【0757】 The server analyzes the workflow and simultaneously evaluates areas for improvement and user stress. For example, it identifies steps where users are losing focus and suggests ways to streamline those steps. 【0758】 Step 7: 【0759】 Based on efficiency suggestions, the server redesigns business procedures and generates an optimized workflow (To-Be). The redesigned procedures also take into account improvements to the user's emotional state. 【0760】 Step 8: 【0761】 The server automatically generates AI agents based on optimized workflows. Before distributing the generated agents to users, simulation tests are performed to ensure they function correctly. 【0762】 Step 9: 【0763】 The generated AI agent is distributed to the user's terminal and applied to subsequent tasks. The AI ​​agent mimics the user's procedures to perform automation, reducing the user's workload. 【0764】 (Example 2) 【0765】 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". 【0766】 While streamlining user procedures in business operations is crucial, traditional methods only partially optimize workflows and fail to consider user emotional burden and psychological stress. Furthermore, generating and distributing automated agents that reflect streamlined workflows presents challenges. Addressing these issues is essential. 【0767】 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. 【0768】 In this invention, the server includes means for acquiring display information from a user terminal, means for analyzing the acquired display information and identifying business procedures, and means for analyzing the user's emotional state and using the emotional information to optimize the flow of activities. This simultaneously achieves increased efficiency in the business flow and reduced emotional burden on the user, and further enables the generation and distribution of automated agents based on the more efficient flow. 【0769】 A "user terminal" is a computer device used by a user, capable of displaying and manipulating data. 【0770】 "Displayed information" refers to digital data displayed on the screen of a user's terminal, and includes some of the information necessary for business operations. 【0771】 A "business procedure" is a sequence of operations and steps that must be followed to perform a specific task. 【0772】 An "activity flow" is a visual representation of business procedures, a diagrammatic representation that shows the structure of the current business process. 【0773】 An "intelligent agent" is a software program created to automate business processes and has the ability to automatically perform repetitive tasks. 【0774】 "Emotional information" refers to data that indicates a user's emotional state, and is psychological information extracted from facial expressions and voice. 【0775】 This invention provides a system that improves work efficiency while reducing the emotional burden on users operating user terminals. The main components of the system are a recording application installed on the user terminal, an emotion analysis engine, and a server for processing this data. 【0776】 User: 【0777】 When a user begins work, they launch a recording application on their terminal. This recording application captures the information displayed on the user's PC screen and collects digital data, including the terminal's operation status. This operation is performed using a standard PC or laptop. 【0778】 Terminal: 【0779】 The emotion analysis engine installed in the device captures facial expressions and voice in real time using the user's video camera and microphone, and extracts the user's emotional information. This allows for the evaluation of stress levels and concentration levels during actual work. The device also uploads the recorded video and emotional data to a server at predetermined intervals. 【0780】 server: 【0781】 The server first analyzes the business procedures using the uploaded data. Next, it generates a current business flow based on the analysis results and visualizes that flow in detail. The server then identifies parts of the business flow that can be made more efficient and proposes ways to optimize the activity flow while taking into account user sentiment information. After optimization is complete, the server automatically generates an intelligent agent and distributes it to the user's terminal. This agent reduces the user's workload by automatically performing repetitive tasks. 【0782】 Specific example: 【0783】 As a concrete example, consider a scenario where a user spends more than three hours using multiple spreadsheet programs for data entry. In this case, we propose a method where an emotion analysis engine detects fatigue from the user's facial expressions, and a server automates part of the task using an intelligent agent to reduce the burden. 【0784】 Example of a prompt: 【0785】 "How can we monitor users' emotional changes during work, analyze their stress levels, and optimize workflows?" 【0786】 This invention makes it possible to improve both operational efficiency and user satisfaction simultaneously. 【0787】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0788】 Step 1: 【0789】 The user launches a recording application on their device. The input is the information displayed on the user's PC screen. The recording application uses this input to capture digital data of the screen in real time. As a result, the device outputs the user's actions and display status as a video file. 【0790】 Step 2: 【0791】 The device uses an emotion analysis engine to capture the user's facial expressions and voice. The input consists of the user's video and audio data. Based on this, the emotion analysis engine extracts the user's emotional information and outputs stress levels and concentration levels as numerical data. 【0792】 Step 3: 【0793】 The device uploads recorded video data and emotion information to the server. The input consists of recorded video data and emotion information. The device sends the data to the server using a secure protocol and outputs a notification when the upload is complete. 【0794】 Step 4: 【0795】 The server analyzes the received video data. The input is video data of the screen display. The server uses a machine learning algorithm to identify business procedures and perform process mapping. The output is a list of identified business procedures and their visualization information. 【0796】 Step 5: 【0797】 The server optimizes business workflows based on received emotional information. Its inputs include emotional information and business procedures. The server generates efficiency suggestions based on the emotional state and designs an optimized workflow. The output consists of the optimization suggestions and the improved workflow. 【0798】 Step 6: 【0799】 The server automatically generates intelligent agents based on optimized business workflows. The input is an optimized business workflow. The server utilizes an AI model to develop agents for business automation and outputs agent files. 【0800】 Step 7: 【0801】 The server distributes the generated intelligent agent to the user terminal. The input is the agent file. The server completes the distribution process and receives output notifying the user that the agent is ready to use. 【0802】 (Application Example 2) 【0803】 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". 【0804】 This invention aims to solve the problem of providing a system that simultaneously improves operational efficiency and manages the emotional state of workers in production sites. In particular, there is a need for operational efficiency improvements that take into account the emotional state of workers, which has not been fully captured by conventional methods for optimizing workflows. 【0805】 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. 【0806】 In this invention, the server includes means for acquiring information from a user terminal, means for monitoring the emotional state of an employee using emotion analysis means, and means for adjusting the workflow based on emotional information. This makes it possible to optimize the workflow while taking into account the emotional state of the employee. 【0807】 A "user terminal" is an electronic device used by a user to retrieve or display information. 【0808】 "Means of acquiring information" refers to methods and devices for collecting necessary data from user terminals. 【0809】 "Means for identifying business procedures" refers to methods or devices for identifying specific business procedures based on acquired information. 【0810】 "Means for generating business process flows" refers to methods or devices for visually creating a business process flow based on identified business procedures. 【0811】 "Means for identifying areas for efficiency improvement" refer to methods and devices for analyzing business workflows and finding areas that can be improved. 【0812】 "Means for designing optimized business workflows" refers to methods or devices for restructuring business workflows based on identified areas for improvement. 【0813】 "Means for automatically generating AI agents" refers to methods or devices for automatically creating artificial intelligence agents according to an optimized workflow. 【0814】 "Means for distributing generated AI agents" refers to methods or devices for sending and installing the created AI agents on user terminals. 【0815】 "Emotional analysis means" refers to methods and devices for extracting and analyzing emotional information from a worker's facial expressions and actions. 【0816】 "Means for adjusting business processes based on emotional information" refers to methods or devices for changing the flow of business processes to an optimal state based on acquired emotional information. 【0817】 To implement this invention, a system is first required to acquire information from a user terminal. This system records user operations and sends the data to a server. The server has a high-performance processor and implements machine learning algorithms for data analysis. Machine learning frameworks such as TensorFlow or PyTorch can be used for this analysis. This allows for the identification of business procedures, and this information is used to visually generate a business flow. 【0818】 Next, in order to use emotion analysis, the user terminal needs to be equipped with a camera and sensors capable of facial recognition and motion analysis. OpenCV and Affectiva technologies can be used for this. The server uses this emotion data to collect emotional information and use it to redesign the workflow. 【0819】 Furthermore, on the server, areas for efficiency improvements are identified, and optimized workflows are designed. Based on this design, an AI agent is automatically generated. This AI agent is then immediately distributed to user terminals and automatically executes the necessary business procedures. 【0820】 As a concrete example of this embodiment, consider a process on a production line with a high defect rate. If the emotion analysis means detects a high stress level in the worker, it re-evaluates the workflow of that process and proposes reducing stress and lowering the defect rate by having the AI ​​agent automate some of the tasks. 【0821】 An example of a prompt message is, "In a factory production line, analyze the factors causing a decrease in work efficiency at a specific process, and generate improvement suggestions based on sentiment data." In this way, it becomes possible to improve both work efficiency and the morale of the workers. 【0822】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0823】 Step 1: 【0824】 The user terminal uses a camera and sensors to capture the worker's facial expressions and movements. This input data is converted into emotional information using a facial recognition algorithm. The output provides the worker's stress level and concentration level. 【0825】 Step 2: 【0826】 The user terminal records real-time operation data and work status, and sends this data to the server. Input data includes keystrokes, mouse movements, and screen display content. The server analyzes this data to identify work procedures and generates a workflow as output. 【0827】 Step 3: 【0828】 The server analyzes the generated business flow using a machine learning algorithm to identify areas for improvement to enhance efficiency. The input is the generated business flow, and the output is the identified areas for efficiency improvement. 【0829】 Step 4: 【0830】 The server designs new workflows and automatically generates AI agents based on the identified areas for improvement. This automated generation process utilizes a generative AI model. The input is information about areas for improvement, and the output is the automatically generated AI agent. 【0831】 Step 5: 【0832】 The server distributes and deploys the generated AI agents to user terminals. The AI ​​agents automatically execute the user's standard work procedures, reducing their workload. The output is the automated business process. 【0833】 Step 6: 【0834】 The server continuously receives feedback from the user terminal and optimizes the AI ​​agent's operation. The input is user feedback information, and the output is the improved AI agent. 【0835】 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. 【0836】 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. 【0837】 In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0838】 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. 【0839】 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. 【0840】 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. 【0841】 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. 【0842】 Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant. 【0843】 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." 【0844】 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. 【0845】 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. 【0846】 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. 【0847】 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. 【0848】 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. 【0849】 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. 【0850】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory. 【0851】 The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor. 【0852】 Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources. 【0853】 Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. 【0854】 The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above. 【0855】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. 【0856】 The following is further disclosed regarding the embodiments described above. 【0857】 (Claim 1) 【0858】 A means of obtaining screen display data from the user terminal, 【0859】 A means of analyzing acquired screen display data to identify business procedures, 【0860】 A means to visualize identified business procedures and generate the current business flow, 【0861】 A means of analyzing business processes to identify areas for improvement, 【0862】 A means of designing an optimized business flow based on identified areas for improvement, 【0863】 A means of automatically generating AI agents based on optimized workflows, 【0864】 A means of distributing the generated AI agent to the user's terminal, 【0865】 A system that includes this. 【0866】 (Claim 2) 【0867】 The system according to claim 1, wherein an AI agent distributed to a user terminal automatically executes a specific business procedure. 【0868】 (Claim 3) 【0869】 The system according to claim 1, comprising means for continuously improving the operation of the AI ​​agent based on user feedback. 【0870】 "Example 1" 【0871】 (Claim 1) 【0872】 An information processing device for recording user operations, 【0873】 A means of obtaining recorded data from the user's terminal, 【0874】 A means for analyzing acquired recorded data and identifying the operating procedure, 【0875】 A means for visualizing identified operation procedures and generating the current operation process, 【0876】 A means of analyzing the operating process to identify areas for improvement, 【0877】 Means for designing an optimized operating process based on identified areas for improvement, 【0878】 A means for automatically generating intelligent agents based on optimized operating processes, 【0879】 A means for transmitting the generated intelligent agent to the user terminal, 【0880】 A system that includes this. 【0881】 (Claim 2) 【0882】 The system according to claim 1, wherein an intelligent agent transmitted to a user terminal automatically executes a specific procedure. 【0883】 (Claim 3) 【0884】 The system according to claim 1, comprising means for continuously improving the behavior of an intelligent agent based on user feedback. 【0885】 "Application Example 1" 【0886】 (Claim 1) 【0887】 Means for acquiring visual information from a user device, 【0888】 A means for analyzing acquired visual information and identifying work procedures, 【0889】 A means for visualizing identified work procedures and generating current work procedures, 【0890】 A means of analyzing work procedures to identify potential for efficiency improvements, 【0891】 Means for designing optimized work procedures based on identified efficiency improvements, 【0892】 A means of automatically generating AI roles based on optimized work procedures, 【0893】 A means for transmitting the generated AI role to the user's device, 【0894】 A system that includes this. 【0895】 (Claim 2) 【0896】 The system according to claim 1, wherein an AI role transmitted to a user device automatically executes a specific work procedure. 【0897】 (Claim 3) 【0898】 The system according to claim 1, comprising means for continuously improving the operation of an AI role based on user responses. 【0899】 "Example 2 of combining an emotion engine" 【0900】 (Claim 1) 【0901】 A means of obtaining display information from the user terminal, 【0902】 A means for analyzing the acquired display information and identifying the business procedure, 【0903】 A means to visualize identified business procedures and generate the current workflow, 【0904】 A means of analyzing the flow of activities to identify areas for improvement, 【0905】 A means of designing an optimized activity flow based on identified areas for improvement, 【0906】 A means for automatically generating intelligent agents based on an optimized activity flow, 【0907】 A means of distributing the generated intelligent agent to the user terminal, 【0908】 A means of analyzing the user's emotional state and using emotional information to optimize the flow of activity, 【0909】 A system that includes this. 【0910】 (Claim 2) 【0911】 The system according to claim 1, wherein an intelligent agent distributed to a user terminal automatically executes a specific business procedure. 【0912】 (Claim 3) 【0913】 The system according to claim 1, comprising means for continuously improving the operation of an intelligent agent based on user feedback. 【0914】 "Application example 2 when combining with an emotional engine" 【0915】 (Claim 1) 【0916】 Means of obtaining information from user terminals, 【0917】 A means of analyzing acquired information and identifying business procedures, 【0918】 A means to visualize identified business procedures and generate the current business flow, 【0919】 A means of analyzing business processes to identify areas for improvement, 【0920】 A means of designing an optimized business flow based on identified areas for improvement, 【0921】 A means of automatically generating AI agents based on optimized workflows, 【0922】 A means of distributing the generated AI agent to the user's terminal, 【0923】 A means of monitoring the emotional state of workers using emotion analysis tools, 【0924】 A means of adjusting the workflow based on emotional information, 【0925】 A system that includes this. 【0926】 (Claim 2) 【0927】 The system according to claim 1, which uses emotion analysis means to automatically provide the user with suggestions for improving work efficiency in specific situations. 【0928】 (Claim 3) 【0929】 The system according to claim 1, comprising means for analyzing emotional information obtained by emotion analysis means and continuously adapting the operation of the AI ​​agent. [Explanation of Symbols] 【0930】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] A means of obtaining screen display data from the user terminal, A means of analyzing acquired screen display data to identify business procedures, A means to visualize identified business procedures and generate the current business flow, A means of analyzing business processes to identify areas for improvement, A means of designing an optimized business flow based on identified areas for improvement, A means of automatically generating AI agents based on optimized workflows, A means of distributing the generated AI agent to the user's terminal, A system that includes this. [Claim 2] The system according to claim 1, wherein an AI agent distributed to a user terminal automatically executes a specific business procedure. [Claim 3] The system according to claim 1, comprising means for continuously improving the operation of the AI ​​agent based on user feedback.

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