system

Abstract

We provide the system. [Solution] Information processing means for collecting business data, Processing means for identifying business processes and generating an optimized process plan by analyzing the aforementioned collected business data, A configuration means for deploying and operating artificial intelligence agents in each business process based on the aforementioned process plan, Control means for monitoring the operation of the artificial intelligence agent and adjusting it based on feedback, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a persona chatbot control method performed by at least one processor, 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 Unexamined Patent Application Publication No. 2022 - 180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 Although the introduction of artificial intelligence agents within an enterprise is a means to promote digital transformation, unplanned introduction results in data being fragmented by department, old agents becoming obsolete, and problems arising such as business bottlenecks. Therefore, there is a problem that it is difficult to achieve unified data utilization across the company and efficient business processes. 【Means for Solving the Problems】 【0005】 The present invention provides a system that includes processing means for collecting business data using information processing means, identifying business processes by applying process mining technology based on that data, and generating an optimal process plan. It also provides configuration means for deploying and operating artificial intelligence agents in each business process based on the generated process plan. Furthermore, it includes control means for continuously monitoring the operation of the artificial intelligence agents and making adjustments based on user feedback, thereby preventing the obsolescence of the artificial intelligence agents, promoting company-wide data utilization, and achieving business process efficiency. 【0006】 "Information processing means" refers to a device or method used to collect business data from various data sources within a company and to analyze that data. 【0007】 "Process mining" is a technique that visualizes the current state of business processes through data analysis and identifies process efficiency and bottlenecks. 【0008】 An "artificial intelligence agent" is autonomous software designed to be integrated into specific business processes to automate and streamline those processes. 【0009】 "Configuration means" refers to a mechanism or device for appropriately positioning and operating artificial intelligence agents based on the generated process plan. 【0010】 A "control system" is a system or method for monitoring the operation of an artificial intelligence agent and for evaluating and adjusting its performance. 【0011】 "Obsolete" refers to a state in which a technology or system loses its effectiveness over time and can no longer meet the latest business requirements. [Brief explanation of the drawing] 【0012】 [Figure 1]This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, when an emotion engine is combined. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention] 【0013】 Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings. 【0014】 First, the terms used in the following description will be explained. 【0015】 In the following embodiments, a tagged 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. 【0016】 In the following embodiments, a tagged RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0017】 In the following embodiments, a tagged 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. 【0018】 In the following embodiments, a tagged 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. 【0019】 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." 【0020】 [First Embodiment] 【0021】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0022】 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. 【0023】 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). 【0024】 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. 【0025】 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. 【0026】 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. 【0027】 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. 【0028】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0029】 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. 【0030】 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. 【0031】 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. 【0032】 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". 【0033】 This invention is a system that utilizes artificial intelligence agents to streamline various business processes within a company. This system operates based on a series of programs designed to efficiently collect and analyze business data scattered throughout the company. 【0034】 Data collection and process mining 【0035】 The server collects business data from terminals in each business department. This data includes transaction information from the sales department, operational status from the manufacturing department, and inventory information. Based on the collected data, the server performs process mining to visualize the current state of business processes and identify bottlenecks. 【0036】 Plans for deploying artificial intelligence agents 【0037】 The server then devises an optimal agent deployment plan based on the results of process mining. For example, it might plan to deploy an AI customer support agent to the sales department, which is spending a lot of time on customer support. 【0038】 Agent deployment and management 【0039】 The terminal installs an artificial intelligence agent into the designated business process according to instructions received from the server. The agent has functions such as automatically responding to customer inquiries and improves business efficiency by operating autonomously. 【0040】 Agent operation and coordination 【0041】 Users utilize the agent's behavior in their daily tasks and evaluate its performance. The server adjusts the agent's behavior based on user feedback, improving and updating its functionality as needed. This continuous improvement process prevents the agent from becoming obsolete and ensures it always meets the latest business requirements. 【0042】 This system enables unified data utilization and efficient business processes across the entire company. 【0043】 The following describes the processing flow. 【0044】 Step 1: 【0045】 The server accesses ERP systems and CRM databases from various terminals within the company to collect business-related data. This data includes customer transaction history, manufacturing process information, and inventory status. 【0046】 Step 2: 【0047】 The server analyzes the collected data using process mining techniques. Specifically, it generates flowcharts of business processes from the data and identifies process bottlenecks by analyzing the time and frequency required for each process. 【0048】 Step 3: 【0049】 Based on the results of process mining, the server develops a plan for deploying the most suitable artificial intelligence agent for each business process. For example, if the sales department spends a long time dealing with customers, it plans to deploy a customer support agent. 【0050】 Step 4: 【0051】 The terminal, following instructions from the server, installs and starts operating an artificial intelligence agent for the specified business process. The agent is designed to support specific tasks, such as automated responses and inventory optimization. 【0052】 Step 5: 【0053】 Users utilize artificial intelligence agents in their work and evaluate their performance. Based on the agent's output, they can assess the degree of improvement in work efficiency. 【0054】 Step 6: 【0055】 The server collects feedback from users and adjusts the operation of the artificial intelligence agent. These adjustments include improving response accuracy and addressing new business requirements. 【0056】 Step 7: 【0057】 The server continuously undergoes functional improvements and updates to prevent the artificial intelligence agent from becoming obsolete. This process ensures that the system can always adapt to the business needs within the company. 【0058】 (Example 1) 【0059】 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." 【0060】 In recent years, business processes within companies have become increasingly complex, making their efficient management and optimization a critical challenge for many. Traditional methods lack a consistent system from the collection and analysis of business data to the deployment and operation of automated agents, and in particular, the continuous improvement and optimization of agents are not adequately carried out. This hinders the improvement of efficiency and the smooth operation of business processes. 【0061】 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. 【0062】 In this invention, the server includes information processing means for collecting business information, processing means for identifying business processes and generating optimized process plans by analyzing the collected business information, and deployment means for deploying and operating automated agents based on the process plan. This makes it possible to efficiently manage business processes within a company and achieve continuous process improvement and optimization. 【0063】 "Business information" refers to all data related to business processes within a company, including transaction information, manufacturing data, inventory status, etc. 【0064】 "Information processing means" refers to devices and software used to effectively collect business information and store it in a database. 【0065】 "Analysis methods" refer to methods and tools used to identify business processes and discover areas for improvement based on collected business information. 【0066】 "Processing means" refers to technologies and methods for generating plans to optimize business processes based on analyzed information. 【0067】 "Process planning" refers to the optimal procedures and strategies set out to streamline business processes. 【0068】 An "automation agent" is software or a system that autonomously handles specific tasks in a business process, and often utilizes artificial intelligence technology. 【0069】 "Deployment means" refers to the methods and technologies for introducing and operating automated agents into appropriate business processes based on process planning. 【0070】 "Control means" refers to methods and techniques for monitoring the operation of an automated agent and adjusting its operation based on feedback as needed. 【0071】 "Improvement measures" refer to technologies and methods for continuously improving and updating the functionality of automated agents. 【0072】 "Generative AI models" refer to technologies that use generative artificial intelligence techniques to build data-based models and propose the best options and strategies for business processes. 【0073】 A "prompt" refers to a series of instructions or questions entered by a user or system to operate a generative AI model. 【0074】 This invention relates to a system for effectively managing and optimizing business processes within a company. The system efficiently processes business information and utilizes automated agents to improve operational efficiency. 【0075】 The server collects business information from each business department using database management systems such as MySQL® and PostgreSQL. This business information includes various types of information necessary for business operations, such as transaction information, manufacturing operation data, and inventory status. Based on the collected information, the server analyzes the data using process analysis techniques (e.g., process mining tools). 【0076】 Based on the analysis results, the server uses a generated AI model to create an optimized business process plan. Based on this plan, the server decides on the deployment of automated agents. For example, deploying a chatbot agent to the customer service department allows for faster responses to customer inquiries and reduces the workload. 【0077】 The terminal uses RPA tools and related software to install and configure agents based on instructions from the server. The agents operate autonomously on the terminal, ensuring smooth execution of business processes. Users evaluate the agent's performance in their daily work and provide feedback to the server. 【0078】 As a concrete example, in the sales department, the AI ​​agent significantly reduced customer response time, enabling them to handle twice as many customers in a single day. Based on this feedback, the server uses a generated AI model to adjust prompt messages and improve the agent's response accuracy. 【0079】 Examples of prompt messages include the following: 【0080】 "Please propose a plan to implement the optimal AI agent in our sales department to streamline the customer service process. Current data includes response time, customer satisfaction, and transaction volume." 【0081】 By using this system, companies can continuously improve their business processes and always meet the latest business requirements. 【0082】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0083】 Step 1: 【0084】 The server collects business information. It uses databases provided from terminals in each business department (e.g., transaction information, manufacturing operation data, inventory status) as input. The collected data is stored in a database management system and forms the basis for subsequent analysis. 【0085】 Step 2: 【0086】 The server analyzes the collected data using process analysis techniques. It uses process mining tools to perform the analysis and identify business processes. The input is business information stored in a database, and the output provides visualization of business processes and identification of bottlenecks. 【0087】 Step 3: 【0088】 The server uses the generated AI model to generate an optimized business process plan. Using the analysis results from step 2 as input, it obtains the optimal process placement proposed by the generated AI model as output. This plan is used to deploy the automation agents. 【0089】 Step 4: 【0090】 The terminal deploys automation agents to specified business processes based on instructions from the server. The input is a business process plan, and the output is an environment where agents are correctly installed and operational. Specifically, RPA tools are used on the terminal to configure and start the agents. 【0091】 Step 5: 【0092】 Users utilize agents in their daily work and evaluate their performance. Inputs include data on agent operation results and work efficiency, while output is feedback that is sent to the server. This feedback is used to determine areas for improvement and the effectiveness of the agents. 【0093】 Step 6: 【0094】 The server retrains the generated AI model and adjusts the agent's behavior based on user feedback. Using feedback data as input, the AI ​​model outputs improved prompts and adjusted agent behavior. This process ensures that the agent is always operating in an optimal state, adapted to business requirements. 【0095】 (Application Example 1) 【0096】 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." 【0097】 In modern manufacturing, identifying and resolving bottlenecks in complex production processes is crucial. Traditional methods suffer from inefficient data collection and analysis, making real-time situational awareness difficult. Furthermore, the operation of artificial intelligence agents presents challenges, such as the difficulty of continuous improvement and the tendency for their performance to become obsolete. 【0098】 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. 【0099】 In this invention, the server includes data processing means for collecting business information, calculation means for identifying business procedures and generating an optimized procedure plan by analyzing the collected business information, and visualization means for monitoring the status of factory operations in real time and identifying bottlenecks. This enables efficient optimization of the manufacturing process and effective operation of artificial intelligence agents. 【0100】 "Business information" is a general term for information such as transaction information, manufacturing status, and inventory information obtained from various business processes carried out within a company. 【0101】 "Data processing means" refers to a series of technical methods and devices for collecting, appropriately storing, and managing business information. 【0102】 "Business procedures" refer to the established procedures, processes, and workflows within a company, contributing to the efficient operation of the business. 【0103】 "Computation means" refers to a device or technology that analyzes collected business information and performs processing to generate an optimal procedure plan. 【0104】 A "procedure plan" is a plan or strategy devised to optimize specific work procedures. 【0105】 "Visualization means" refers to technologies or devices that visually display the progress and status of factory operations in real time, and that clearly identify bottlenecks. 【0106】 A "bottleneck" refers to a specific part or factor in a business process that causes delays or reduced efficiency. 【0107】 "Management and control means" refers to management systems and technologies for monitoring the operation of artificial intelligence agents and making adjustments as needed. 【0108】 This invention relates to a system aimed at improving the efficiency of business processes in a manufacturing environment. The server collects business information generated within the factory through sensors and terminals. This information includes the operating status of the production line, equipment usage data, inventory information, and so on. 【0109】 The server processes and analyzes the collected data using data analysis tools such as Python. The analysis results identify business procedures through process mining techniques, and an optimized procedure plan is generated. By using process mining software such as Celonis, the manufacturing process can be visualized, making it easier to identify bottlenecks. 【0110】 The visualization results are displayed on the device via visualization tools such as Tableau. This allows users to monitor the situation on the manufacturing floor in real time and respond immediately if an anomaly occurs. 【0111】 Furthermore, artificial intelligence agents are strategically deployed to automate business processes. Through management and control mechanisms, agent behavior is continuously monitored and adjusted, and alerts can be sent to users using notification functions such as Twilio. 【0112】 For example, if a delay in material supply is detected on a particular manufacturing line, the server immediately sends out a notification and proposes relocating the material supply agent as a countermeasure. If the user implements this improvement appropriately, it will enhance the overall efficiency of the manufacturing process. 【0113】 By utilizing a generative AI model, and using an example prompt such as, "Analyze the data from this factory's production line and visualize the causes of delays and solutions using process mining," efficient system operation becomes possible. 【0114】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0115】 Step 1: 【0116】 The server collects operational information from sensors and terminals within the factory. Input data includes manufacturing line operating status, equipment usage data, and inventory information. This data is converted into a specific format and stored in a database suitable for analysis. 【0117】 Step 2: 【0118】 The server processes the collected data using Python data analysis libraries (such as Pandas and NumPy). Specifically, it performs data imputation and removal of outliers to generate a clean dataset. This clean data is then used for subsequent process mining. 【0119】 Step 3: 【0120】 The server uses process mining techniques to identify business procedures from clean data and generate an optimized procedure plan. This process utilizes process mining tools like Celonis to visualize the flow and bottlenecks of business procedures. The output is an optimized procedure plan. 【0121】 Step 4: 【0122】 The server deploys artificial intelligence agents based on the generated procedure plan and initiates the automated process. During this process, the agents' operation is optimized, focusing on bottlenecks identified in the plan to ensure efficient operation. The agents autonomously perform their scheduled tasks and provide progress information to the server. 【0123】 Step 5: 【0124】 The terminal uses visualization tools such as Tableau to display the generated procedure plan and agent operation status in real time. Based on this visualized information, users can understand the current situation on the manufacturing floor and take immediate action if any abnormalities are detected. 【0125】 Step 6: 【0126】 The server continuously monitors the agent's operation using management and control mechanisms and makes adjustments as needed. Specifically, it receives user feedback and abnormal data, and uses AI models to improve the agent's operation. It also sends alerts to users using notification functions such as Twilio. 【0127】 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. 【0128】 This invention provides an artificial intelligence agent system for optimizing and autonomously operating business processes within a company, and further enhances the system's responsiveness and adaptability by incorporating an emotion engine that recognizes user emotions. 【0129】 Data collection and process mining 【0130】 The server collects business data from terminals in each business department. This data includes transaction information from the sales department and logs related to the manufacturing process from the manufacturing department. The server analyzes this data using process mining techniques. Based on the analysis results, it identifies business processes and generates an optimal process plan. 【0131】 Introduction of artificial intelligence agents 【0132】 The server deploys artificial intelligence agents based on the process plan and begins operations in each process. For example, in customer support, agents are used to respond quickly to user inquiries. 【0133】 Emotional engine integration 【0134】 Furthermore, by incorporating an emotion engine into this system, the system can recognize the user's emotional state and feed that data back into the agent's response. For example, if the emotion engine determines that the user is stressed, the information and responses provided by the agent can be changed. 【0135】 Feedback and Improvement 【0136】 Users can evaluate the agent's output and emotional responses in their work. The server adjusts the agent's behavior and emotion engine settings based on this feedback. This continuous improvement process ensures that the system always adapts to user needs and prevents agent obsolescence. 【0137】 This configuration makes it possible to achieve efficient business processes while taking user emotions into consideration, thereby supporting improved productivity across the entire company. 【0138】 The following describes the processing flow. 【0139】 Step 1: 【0140】 The server collects necessary business data from each terminal within the company via ERP systems and CRM databases. This data includes customer transaction history, inventory status, and manufacturing process logs. 【0141】 Step 2: 【0142】 The server analyzes the collected business data using process mining algorithms to identify each business process and evaluate its efficiency. Based on the analysis results, it generates a process plan to improve bottleneck processes. 【0143】 Step 3: 【0144】 Based on the generated process plan, the server selects the most suitable artificial intelligence agent for each business process and instructs the terminal to install it. This agent plays a role in streamlining tasks such as customer support inquiries and manufacturing inventory management. 【0145】 Step 4: 【0146】 The terminal, following instructions from the server, installs agents in the specified order of business processes and begins operation. The agents continuously execute algorithms to optimize operations and autonomously continue tasks that were initially configured for their specific roles. 【0147】 Step 5: 【0148】 The user interacts with the operational artificial intelligence agent to check the progress of their tasks. The emotion engine analyzes the user's emotions in real time, and if, for example, the user is feeling stressed, the agent's response is flexibly adjusted accordingly. 【0149】 Step 6: 【0150】 The server collects feedback from user experience and sentiment analysis, and updates the settings of the artificial intelligence agent and emotion engine. This feedback loop allows each agent to be continuously improved, leading to enhanced agent performance and a higher quality user experience. 【0151】 Step 7: 【0152】 The server combines the analysis results from the emotion engine with business data to formulate and implement a company-wide process optimization strategy. This strategy aims to improve efficiency across the entire enterprise, and as needed, it involves large-scale updates and expansions of agents and processes. 【0153】 (Example 2) 【0154】 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." 【0155】 While there is a demand for increased efficiency in business processes, a challenge remains in ensuring that agents respond appropriately to users' emotions and improve the flexibility and usability of those processes. To achieve this, a proper understanding of business procedures, the creation of optimized plans, and the autonomous operation of intelligent programs are essential. 【0156】 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. 【0157】 In this invention, the server includes data acquisition means for collecting business information, information analysis means for analyzing the acquired business information, identifying business procedures, and generating an optimized procedure plan, and deployment means for deploying and operating intelligent programs to each business procedure based on the procedure plan. This enables more efficient and flexible operation of business processes. 【0158】 "Data acquisition means" refers to technology equipped with functions for effectively collecting and processing business information. 【0159】 "Information analysis means" refers to technologies for analyzing collected business information, identifying business procedures, and generating optimized plans. 【0160】 A "deployment mechanism" is a mechanism for deploying and operating an intelligent program at each step of a business procedure based on the generated procedure plan. 【0161】 "Emotion recognition function" is a technology that detects the user's emotional state and reflects it in the response of the intelligent program. 【0162】 "Control means" refers to the technology that manages the process of monitoring the operation of an intelligent program and adjusting settings and parameters based on feedback. 【0163】 This invention is a system for autonomously optimizing and operating a company's business processes. Its embodiments are described in detail below. 【0164】 First, the server collects business information from terminals in each business department within the company. This information collection uses a communication protocol to send the information to a database via a network connection. The information collected includes data such as transaction history from the sales department and process data from the manufacturing department. 【0165】 Next, the server analyzes the collected information using "information analysis tools." At this stage, general business process analysis software is used, for example, utilizing open-source process mining tools to visualize business procedures and generate optimized plans. 【0166】 In each business process, the server deploys artificial intelligence agents using a "deployment method." These agents are typically implemented using cloud-based AI services and are configured specifically to interact with users using natural language processing. In this process, the system utilizes a generative AI model to provide quick and appropriate responses based on user input. 【0167】 Furthermore, the server integrates "emotion recognition functionality" into the agent, allowing it to determine the user's emotional state and reflect it in its response. For example, it can adjust the tone and content of the response to provide a better user experience. 【0168】 Finally, the system continuously collects user feedback and adjusts its intelligent program using "control mechanisms." This ensures that the system is always adaptable to the latest business requirements and enables continuous improvement of business processes. 【0169】 As a concrete example, consider a customer support scenario. When a user enters a prompt such as, "To improve customer support operations, please explain how agents determine a user's emotions and provide diverse responses," the system can then provide the user with the most appropriate information and procedures based on that input. 【0170】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0171】 Step 1: 【0172】 The server collects business information from business terminals. This information collection automatically retrieves transaction data, process logs, and other data from terminals in each department via the network. The input is business data transmitted from the terminals, and the output is an integrated database stored on the server. This allows for the aggregation of business information across the entire company. 【0173】 Step 2: 【0174】 The server analyzes the collected business information using "information analysis tools." Specifically, it uses open-source process mining software to identify business procedures. The input is business information stored in an integrated database, and the output is the analyzed process flow and optimized business plan. This reveals inefficiencies in the current process. 【0175】 Step 3: 【0176】 The server deploys artificial intelligence agents based on an optimized work plan. Deployment utilizes cloud-based AI services and loads natural language processing models to enable user interaction. The input is the optimized work plan, and the output is the agent setup status adapted to each work step. This allows the agents to begin handling the work. 【0177】 Step 4: 【0178】 The server integrates "emotion recognition functionality" into the agent, adjusting its response according to the user's emotions. Specifically, it uses an emotion analysis tool to analyze the user's input text. The input is the user's inquiry or feedback, and the output is the analyzed emotional state. Based on this, the agent takes the most appropriate action for the user. 【0179】 Step 5: 【0180】 Users evaluate the agent's service quality and provide feedback. This feedback is sent to the server, which then adjusts the agent's response patterns and sentiment settings based on it. The input is user evaluation data, and the output is the improved agent response settings. This allows for continuous improvement of service quality. 【0181】 (Application Example 2) 【0182】 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". 【0183】 This invention aims to improve both operational efficiency and user satisfaction simultaneously by enabling appropriate responses that respond to user emotions in business processes within companies. Conventional systems often fail to adequately consider user emotions, resulting in a decline in the quality of business processes and responses. The challenge lies in resolving this issue and achieving more adaptive and effective business operations. 【0184】 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. 【0185】 In this invention, the server includes information processing means for collecting business data; processing means for identifying business processes and generating optimized process plans by analyzing the collected business data; configuration means for deploying and operating general-purpose intelligent agents in each business process based on the process plan; management means for monitoring the operation of the general-purpose intelligent agents and adjusting them based on feedback; and emotion analysis means for analyzing the user's psychological state and reflecting that information in the responses of the general-purpose intelligent agents. This enables appropriate optimization of business processes and personalized responses that take into account the user's emotions. 【0186】 "Information processing means" refers to a device or method that collects and analyzes business data to support the identification and optimization of business processes. 【0187】 "Processing means" refers to an apparatus or method for analyzing collected business data to identify business processes and generate an optimized process plan. 【0188】 "Configuration means" refers to a device or method that deploys general-purpose intelligent agents to each business process and executes operations based on an optimized process plan. 【0189】 "Management means" refers to a device or method for monitoring the operation of a general-purpose intelligent agent and adjusting the agent's operation based on feedback. 【0190】 "Emotional analysis means" refers to a device or method that analyzes the psychological state of a user and uses that information to adapt the response of a general-purpose intelligent agent. 【0191】 As a means of implementing this invention, a system that utilizes the technology infrastructure within a company is proposed. The server uses information processing means to collect business data from terminals in each business department. The collected data includes transaction information from sales and work logs from the manufacturing department. This data is analyzed by data analysis software using Python or Pandas, business processes are identified using process mining techniques, and an optimized process plan is generated. 【0192】 Based on the generated process plan, the server deploys general-purpose intelligent agents to each business process and begins operation using configuration methods. This involves agents using AI models, and real-time communication using WebSocket is performed for overall system coordination. 【0193】 Furthermore, feedback tailored to the user's emotions is reflected in the agent through an emotion analysis system that analyzes the user's psychological state in real time. This process is performed using natural language processing models such as Hugging Face Transformers. The system receives user feedback through a management system and uses it as data for evaluation and improvement. 【0194】 As a concrete example, in a video streaming application, if the system analyzes that a user is experiencing stress, the server will recommend enjoyable content. In this case, the generative AI model can be prompted with a prompt such as, "Suggest video genres that match the user's desired emotions," providing instructions for appropriate content recommendations. This system enables personalized responses tailored to each user's individual emotions. 【0195】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0196】 Step 1: 【0197】 The server collects business data from terminals in each business department. This includes transaction information from the sales department and work logs from the manufacturing department. The collected data is used as input by an information processing system and formatted into an appropriate format. The formatted business data is then output. 【0198】 Step 2: 【0199】 The server analyzes formatted business data using process mining techniques. It analyzes the data using Python and Pandas to identify business processes. Using formatted business data as input, it generates the identified business processes as output. Specifically, it performs data pattern recognition and statistical analysis. 【0200】 Step 3: 【0201】 The server generates an optimized process plan based on the identified business processes. It utilizes processing tools and AI models to perform calculations to optimize the processes. The input data is the identified business processes, and the output is the optimized process plan. The operation includes simulating and evaluating multiple process options. 【0202】 Step 4: 【0203】 The server deploys and operates general-purpose intelligent agents to each business process based on an optimized process plan. Using a configuration method, it communicates in real time via WebSocket and directs the agents to operate according to instructions. The input is the optimized process plan, and the output is the results of the agent's operation. Specifically, it initiates agents and sends commands. 【0204】 Step 5: 【0205】 The server analyzes the user's psychological state using emotion analysis tools. It uses natural language processing models such as Hugging Face Transformers to convert user voice and text data into emotion data. The input data is the user's communication log, and the output is the user's emotional state. Specifically, it performs voice analysis and text emotion analysis. 【0206】 Step 6: 【0207】 The server reflects the analyzed user's emotional state in the operation of the aforementioned agent. Using management tools, it generates responses adapted to the emotion and provides feedback to the agent. The input is the user's emotional state, and the output is the agent's response result. The prompt is "Generate a response that matches the emotion the user desires." The specific actions involve generating or modifying the response. 【0208】 Step 7: 【0209】 The user receives the agent's response and evaluates it. The server processes the evaluation results using management tools and uses them for continuous system improvement. The input data is the user's evaluation, and the output is the improved agent performance. Specific operations include collecting and analyzing feedback. 【0210】 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. 【0211】 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. 【0212】 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. 【0213】 [Second Embodiment] 【0214】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0215】 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. 【0216】 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). 【0217】 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. 【0218】 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. 【0219】 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). 【0220】 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. 【0221】 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. 【0222】 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. 【0223】 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. 【0224】 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. 【0225】 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". 【0226】 This invention is a system that utilizes artificial intelligence agents to streamline various business processes within a company. This system operates based on a series of programs designed to efficiently collect and analyze business data scattered throughout the company. 【0227】 Data collection and process mining 【0228】 The server collects business data from terminals in each business department. This data includes transaction information from the sales department, operational status from the manufacturing department, and inventory information. Based on the collected data, the server performs process mining to visualize the current state of business processes and identify bottlenecks. 【0229】 Plans for deploying artificial intelligence agents 【0230】 The server then devises an optimal agent deployment plan based on the results of process mining. For example, it might plan to deploy an AI customer support agent to the sales department, which is spending a lot of time on customer support. 【0231】 Agent deployment and management 【0232】 The terminal installs an artificial intelligence agent into the designated business process according to instructions received from the server. The agent has functions such as automatically responding to customer inquiries and improves business efficiency by operating autonomously. 【0233】 Agent operation and coordination 【0234】 Users utilize the agent's behavior in their daily tasks and evaluate its performance. The server adjusts the agent's behavior based on user feedback, improving and updating its functionality as needed. This continuous improvement process prevents the agent from becoming obsolete and ensures it always meets the latest business requirements. 【0235】 This system enables unified data utilization and efficient business processes across the entire company. 【0236】 The following describes the processing flow. 【0237】 Step 1: 【0238】 The server accesses ERP systems and CRM databases from various terminals within the company to collect business-related data. This data includes customer transaction history, manufacturing process information, and inventory status. 【0239】 Step 2: 【0240】 The server analyzes the collected data using process mining techniques. Specifically, it generates flowcharts of business processes from the data and identifies process bottlenecks by analyzing the time and frequency required for each process. 【0241】 Step 3: 【0242】 Based on the results of process mining, the server develops a plan for deploying the most suitable artificial intelligence agent for each business process. For example, if the sales department spends a long time dealing with customers, it plans to deploy a customer support agent. 【0243】 Step 4: 【0244】 The terminal, following instructions from the server, installs and starts operating an artificial intelligence agent for the specified business process. The agent is designed to support specific tasks, such as automated responses and inventory optimization. 【0245】 Step 5: 【0246】 Users utilize artificial intelligence agents in their work and evaluate their performance. Based on the agent's output, they can assess the degree of improvement in work efficiency. 【0247】 Step 6: 【0248】 The server collects feedback from users and adjusts the operation of the artificial intelligence agent. These adjustments include improving response accuracy and addressing new business requirements. 【0249】 Step 7: 【0250】 The server continuously undergoes functional improvements and updates to prevent the artificial intelligence agent from becoming obsolete. This process ensures that the system can always adapt to the business needs within the company. 【0251】 (Example 1) 【0252】 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." 【0253】 In recent years, business processes within companies have become increasingly complex, making their efficient management and optimization a critical challenge for many. Traditional methods lack a consistent system from the collection and analysis of business data to the deployment and operation of automated agents, and in particular, the continuous improvement and optimization of agents are not adequately carried out. This hinders the improvement of efficiency and the smooth operation of business processes. 【0254】 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. 【0255】 In this invention, the server includes information processing means for collecting business information, processing means for identifying business processes and generating optimized process plans by analyzing the collected business information, and deployment means for deploying and operating automated agents based on the process plan. This makes it possible to efficiently manage business processes within a company and achieve continuous process improvement and optimization. 【0256】 "Business information" refers to all data related to business processes within a company, including transaction information, manufacturing data, inventory status, etc. 【0257】 "Information processing means" refers to devices and software used to effectively collect business information and store it in a database. 【0258】 "Analysis methods" refer to methods and tools used to identify business processes and discover areas for improvement based on collected business information. 【0259】 "Processing means" refers to technologies and methods for generating plans to optimize business processes based on analyzed information. 【0260】 "Process planning" refers to the optimal procedures and strategies set out to streamline business processes. 【0261】 An "automation agent" is software or a system that autonomously handles specific tasks in a business process, and often utilizes artificial intelligence technology. 【0262】 "Deployment means" refers to the methods and technologies for introducing and operating automated agents into appropriate business processes based on process planning. 【0263】 "Control means" refers to methods and techniques for monitoring the operation of an automated agent and adjusting its operation based on feedback as needed. 【0264】 "Improvement measures" refer to technologies and methods for continuously improving and updating the functionality of automated agents. 【0265】 "Generative AI models" refer to technologies that use generative artificial intelligence techniques to build data-based models and propose the best options and strategies for business processes. 【0266】 A "prompt" refers to a series of instructions or questions entered by a user or system to operate a generative AI model. 【0267】 This invention relates to a system for effectively managing and optimizing business processes within a company. The system efficiently processes business information and utilizes automated agents to improve operational efficiency. 【0268】 The server uses database management systems such as MySQL and PostgreSQL to collect business information from each business department. This business information includes various types of information necessary for business operations, such as transaction information, manufacturing operation data, and inventory status. Based on the collected information, the server analyzes the data using process analysis techniques (e.g., process mining tools). 【0269】 Based on the analysis results, the server uses a generated AI model to create an optimized business process plan. Based on this plan, the server decides on the deployment of automated agents. For example, deploying a chatbot agent to the customer service department allows for faster responses to customer inquiries and reduces the workload. 【0270】 The terminal uses RPA tools and related software to install and configure agents based on instructions from the server. The agents operate autonomously on the terminal, ensuring smooth execution of business processes. Users evaluate the agent's performance in their daily work and provide feedback to the server. 【0271】 As a concrete example, in the sales department, the AI ​​agent significantly reduced customer response time, enabling them to handle twice as many customers in a single day. Based on this feedback, the server uses a generated AI model to adjust prompt messages and improve the agent's response accuracy. 【0272】 Examples of prompt messages include the following: 【0273】 "Please propose a plan to implement the optimal AI agent in our sales department to streamline the customer service process. Current data includes response time, customer satisfaction, and transaction volume." 【0274】 By using this system, companies can continuously improve their business processes and always meet the latest business requirements. 【0275】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0276】 Step 1: 【0277】 The server collects business information. It uses databases provided from terminals in each business department (e.g., transaction information, manufacturing operation data, inventory status) as input. The collected data is stored in a database management system and forms the basis for subsequent analysis. 【0278】 Step 2: 【0279】 The server analyzes the collected data using process analysis techniques. It uses process mining tools to perform the analysis and identify business processes. The input is business information stored in a database, and the output provides visualization of business processes and identification of bottlenecks. 【0280】 Step 3: 【0281】 The server uses the generated AI model to generate an optimized business process plan. Using the analysis results from step 2 as input, it obtains the optimal process placement proposed by the generated AI model as output. This plan is used to deploy the automation agents. 【0282】 Step 4: 【0283】 Based on the instructions from the server, the terminal deploys an automation agent to the specified business process. The input is the business process plan, and the output is an environment where the agent is correctly installed and operational. Specifically, on the terminal, the RPA tool is used to configure and start the agent. 【0284】 Step 5: 【0285】 The user utilizes the agent in daily operations and evaluates its performance. The input uses the operation results of the agent and data on business efficiency, and the output generates feedback that is sent to the server. This feedback determines the improvement points and effectiveness of the agent. 【0286】 Step 6: 【0287】 Based on the feedback from the user, the server retrains the generative AI model to adjust the operation of the agent. The input uses the feedback data, and the output is the improved prompt text of the AI model and the adjusted agent operation. This process enables the agent to always be operated in an optimal state adapted to the business requirements. 【0288】 (Application Example 1) 【0289】 Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal". 【0290】 In modern manufacturing, it is required to identify and eliminate bottlenecks in complex production processes. With conventional methods, the efficiency of data collection and analysis is low, and it is difficult to grasp the situation in real time. Also, in the operation of artificial intelligence agents, there is a problem that continuous improvement is difficult and their performance tends to become obsolete. 【0291】 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. 【0292】 In this invention, the server includes data processing means for collecting business information, calculation means for identifying business procedures and generating an optimized procedure plan by analyzing the collected business information, and visualization means for monitoring the status of factory operations in real time and identifying bottlenecks. This enables efficient optimization of the manufacturing process and effective operation of artificial intelligence agents. 【0293】 "Business information" is a general term for information such as transaction information, manufacturing status, and inventory information obtained from various business processes carried out within a company. 【0294】 "Data processing means" refers to a series of technical methods and devices for collecting, appropriately storing, and managing business information. 【0295】 "Business procedures" refer to the established procedures, processes, and workflows within a company, contributing to the efficient operation of the business. 【0296】 "Computation means" refers to a device or technology that analyzes collected business information and performs processing to generate an optimal procedure plan. 【0297】 A "procedure plan" is a plan or strategy devised to optimize specific work procedures. 【0298】 "Visualization means" refers to technologies or devices that visually display the progress and status of factory operations in real time, and that clearly identify bottlenecks. 【0299】 A "bottleneck" refers to a specific part or factor in a business process that causes delays or reduced efficiency. 【0300】 "Management and control means" refers to management systems and technologies for monitoring the operation of artificial intelligence agents and making adjustments as needed. 【0301】 This invention relates to a system aimed at improving the efficiency of business processes in a manufacturing environment. The server collects business information generated within the factory through sensors and terminals. This information includes the operating status of the production line, equipment usage data, inventory information, and so on. 【0302】 The server processes and analyzes the collected data using data analysis tools such as Python. The analysis results identify business procedures through process mining techniques, generating optimized procedure plans. By using process mining software such as Celonis, the manufacturing process can be visualized, making it easier to identify bottlenecks. 【0303】 The visualization results are displayed on the device via visualization tools such as Tableau. This allows users to monitor the situation on the manufacturing floor in real time and respond immediately if an anomaly occurs. 【0304】 Furthermore, artificial intelligence agents are strategically deployed to automate business processes. Through management and control mechanisms, agent behavior is continuously monitored and adjusted, and alerts can be sent to users using notification functions such as Twilio. 【0305】 For example, if a delay in material supply is detected on a particular manufacturing line, the server immediately sends out a notification and proposes relocating the material supply agent as a countermeasure. If the user implements this improvement appropriately, it will enhance the overall efficiency of the manufacturing process. 【0306】 By utilizing a generative AI model, and using an example prompt such as, "Analyze the data from this factory's production line and visualize the causes of delays and solutions using process mining," efficient system operation becomes possible. 【0307】 The flow of the specific process in Application Example 1 will be described using FIG. 12. 【0308】 Step 1: 【0309】 The server collects business information from sensors and terminals in the factory. The input data includes the operating status of the production line, equipment usage data, inventory information, etc. These data are converted into a certain format and stored in the database in a form suitable for analysis. 【0310】 Step 2: 【0311】 The server processes the collected data using Python data analysis libraries (such as Pandas, NumPy, etc.). Specifically, it complements missing data and removes outliers to generate a clean dataset. This clean data is used for subsequent process mining. 【0312】 Step 3: 【0313】 The server uses process mining technology to identify business procedures from the clean data and generate an optimized procedure plan. In this process, a process mining tool such as Celonis is used to visualize the flow and bottlenecks of the business procedures. As output, an optimized procedure plan is obtained. 【0314】 Step 4: 【0315】 The server deploys artificial intelligence agents based on the generated procedure plan and starts an automated process. At this time, the operation is optimized with emphasis on the bottlenecks identified in the plan so that the agents can operate efficiently. The agents autonomously execute the scheduled tasks and provide the progress information to the server. 【0316】 Step 5: 【0317】 The terminal uses visualization tools such as Tableau to display the generated procedure plan and agent operation status in real time. Based on this visualized information, users can understand the current situation on the manufacturing floor and take immediate action if any abnormalities are detected. 【0318】 Step 6: 【0319】 The server continuously monitors the agent's operation using management and control mechanisms and makes adjustments as needed. Specifically, it receives user feedback and abnormal data, and uses AI models to improve the agent's operation. It also sends alerts to users using notification functions such as Twilio. 【0320】 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. 【0321】 This invention provides an artificial intelligence agent system for optimizing and autonomously operating business processes within a company, and further enhances the system's responsiveness and adaptability by incorporating an emotion engine that recognizes user emotions. 【0322】 Data collection and process mining 【0323】 The server collects business data from terminals in each business department. This data includes transaction information from the sales department and logs related to the manufacturing process from the manufacturing department, and the server analyzes this data using process mining techniques. Based on the analysis results, it identifies business processes and generates an optimal process plan. 【0324】 Introduction of artificial intelligence agents 【0325】 The server deploys artificial intelligence agents based on the process plan and begins operations in each process. For example, in customer support, agents are used to respond quickly to user inquiries. 【0326】 Emotional engine integration 【0327】 Furthermore, by incorporating an emotion engine into this system, the system can recognize the user's emotional state and feed that data back into the agent's response. For example, if the emotion engine determines that the user is stressed, the information and responses provided by the agent can be changed. 【0328】 Feedback and Improvement 【0329】 Users can evaluate the agent's output and emotional responses in their work. The server adjusts the agent's behavior and emotion engine settings based on this feedback. This continuous improvement process ensures that the system always adapts to user needs and prevents agent obsolescence. 【0330】 This configuration makes it possible to achieve efficient business processes while taking user emotions into consideration, thereby supporting improved productivity across the entire company. 【0331】 The following describes the processing flow. 【0332】 Step 1: 【0333】 The server collects necessary business data from each terminal within the company through ERP systems and CRM databases. This data includes customer transaction history, inventory status, and manufacturing process logs. 【0334】 Step 2: 【0335】 The server analyzes the collected business data using process mining algorithms to identify each business process and evaluate its efficiency. Based on the analysis results, it generates a process plan to improve bottleneck processes. 【0336】 Step 3: 【0337】 Based on the generated process plan, the server selects the most suitable artificial intelligence agent for each business process and instructs the terminal to install it. This agent is responsible for streamlining tasks such as customer support inquiries and manufacturing inventory management. 【0338】 Step 4: 【0339】 The terminal, following instructions from the server, installs agents in the specified order of business processes and begins operation. The agents continuously execute algorithms to optimize operations and autonomously continue tasks that were initially configured for their specific roles. 【0340】 Step 5: 【0341】 The user interacts with the operational artificial intelligence agent to check the progress of their tasks. The emotion engine analyzes the user's emotions in real time, and if, for example, the user is feeling stressed, the agent's response is flexibly adjusted accordingly. 【0342】 Step 6: 【0343】 The server collects feedback from user experience and sentiment analysis, and updates the settings of the artificial intelligence agent and emotion engine. This feedback loop allows each agent to be continuously improved, leading to enhanced agent performance and a higher quality user experience. 【0344】 Step 7: 【0345】 The server combines the analysis results from the emotion engine with business data to formulate and implement a company-wide process optimization strategy. This strategy aims to improve efficiency across the entire enterprise, and as needed, it involves large-scale updates and expansions of agents and processes. 【0346】 (Example 2) 【0347】 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". 【0348】 While there is a demand for increased efficiency in business processes, a challenge remains in ensuring that agents respond appropriately to users' emotions and improve the flexibility and usability of those processes. To achieve this, a proper understanding of business procedures, the creation of optimized plans, and the autonomous operation of intelligent programs are essential. 【0349】 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. 【0350】 In this invention, the server includes data acquisition means for collecting business information, information analysis means for analyzing the acquired business information, identifying business procedures, and generating an optimized procedure plan, and deployment means for deploying and operating intelligent programs to each business procedure based on the procedure plan. This enables more efficient and flexible operation of business processes. 【0351】 "Data acquisition means" refers to technology equipped with functions for effectively collecting and processing business information. 【0352】 "Information analysis means" refers to technologies for analyzing collected business information, identifying business procedures, and generating optimized plans. 【0353】 A "deployment mechanism" is a mechanism for deploying and operating an intelligent program at each step of a business procedure based on the generated procedure plan. 【0354】 "Emotion recognition function" is a technology that detects the user's emotional state and reflects it in the response of the intelligent program. 【0355】 "Control means" refers to the technology that manages the process of monitoring the operation of an intelligent program and adjusting settings and parameters based on feedback. 【0356】 This invention is a system for autonomously optimizing and operating a company's business processes. Its embodiments are described in detail below. 【0357】 First, the server collects business information from terminals in each business department within the company. This information collection uses a communication protocol to send the information to a database via a network connection. The information collected includes data such as transaction history from the sales department and process data from the manufacturing department. 【0358】 Next, the server analyzes the collected information using "information analysis tools." At this stage, general business process analysis software is used, for example, utilizing open-source process mining tools to visualize business procedures and generate optimized plans. 【0359】 In each business process, the server deploys artificial intelligence agents using a "deployment method." These agents are typically implemented using cloud-based AI services and are configured specifically to interact with users using natural language processing. In this process, the system utilizes a generative AI model to provide quick and appropriate responses based on user input. 【0360】 Furthermore, the server integrates "emotion recognition functionality" into the agent, allowing it to determine the user's emotional state and reflect it in its response. For example, it can adjust the tone and content of the response to provide a better user experience. 【0361】 Finally, the system continuously collects user feedback and adjusts its intelligent program using "control mechanisms." This ensures that the system is always adaptable to the latest business requirements and enables continuous improvement of business processes. 【0362】 As a concrete example, consider a customer support scenario. When a user enters a prompt such as, "To improve customer support operations, please explain how agents determine a user's emotions and provide diverse responses," the system can then provide the user with the most appropriate information and procedures based on that input. 【0363】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0364】 Step 1: 【0365】 The server collects business information from business terminals. This information collection automatically retrieves transaction data, process logs, and other data from terminals in each department via the network. The input is business data transmitted from the terminals, and the output is an integrated database stored on the server. This allows for the aggregation of business information across the entire company. 【0366】 Step 2: 【0367】 The server analyzes the collected business information using "information analysis tools." Specifically, it uses open-source process mining software to identify business procedures. The input is business information stored in an integrated database, and the output is the analyzed process flow and optimized business plan. This reveals inefficiencies in the current process. 【0368】 Step 3: 【0369】 The server deploys artificial intelligence agents based on an optimized work plan. Deployment utilizes cloud-based AI services and loads natural language processing models to enable user interaction. The input is the optimized work plan, and the output is the agent setup status adapted to each work step. This allows the agents to begin handling the work. 【0370】 Step 4: 【0371】 The server integrates "emotion recognition functionality" into the agent, adjusting its response according to the user's emotions. Specifically, it uses an emotion analysis tool to analyze the user's input text. The input is the user's inquiry or feedback, and the output is the analyzed emotional state. Based on this, the agent takes the most appropriate action for the user. 【0372】 Step 5: 【0373】 Users evaluate the agent's service quality and provide feedback. This feedback is sent to the server, which then adjusts the agent's response patterns and sentiment settings based on it. The input is user evaluation data, and the output is the improved agent response settings. This allows for continuous improvement of service quality. 【0374】 (Application Example 2) 【0375】 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." 【0376】 This invention aims to improve both operational efficiency and user satisfaction simultaneously by enabling appropriate responses that respond to user emotions in business processes within companies. Conventional systems often fail to adequately consider user emotions, resulting in a decline in the quality of business processes and responses. The challenge lies in resolving this issue and achieving more adaptive and effective business operations. 【0377】 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. 【0378】 In this invention, the server includes information processing means for collecting business data; processing means for identifying business processes and generating optimized process plans by analyzing the collected business data; configuration means for deploying and operating general-purpose intelligent agents for each business process based on the process plan; management means for monitoring the operation of the general-purpose intelligent agents and adjusting them based on feedback; and emotion analysis means for analyzing the user's psychological state and reflecting that information in the responses of the general-purpose intelligent agents. This enables appropriate optimization of business processes and personalized responses that take into account the user's emotions. 【0379】 "Information processing means" refers to a device or method that collects and analyzes business data to support the identification and optimization of business processes. 【0380】 "Processing means" refers to an apparatus or method for analyzing collected business data to identify business processes and generate an optimized process plan. 【0381】 "Configuration means" refers to a device or method that deploys general-purpose intelligent agents to each business process and executes operations based on an optimized process plan. 【0382】 "Management means" refers to a device or method for monitoring the operation of a general-purpose intelligent agent and adjusting the agent's operation based on feedback. 【0383】 "Emotional analysis means" refers to a device or method that analyzes the psychological state of a user and uses that information to adapt the response of a general-purpose intelligent agent. 【0384】 As a means of implementing this invention, a system that utilizes the technology infrastructure within a company is proposed. The server uses information processing means to collect business data from terminals in each business department. The collected data includes transaction information from sales and work logs from the manufacturing department. This data is analyzed by data analysis software using Python or Pandas, business processes are identified using process mining techniques, and an optimized process plan is generated. 【0385】 Based on the generated process plan, the server deploys general-purpose intelligent agents to each business process and begins operation using configuration methods. This involves agents using AI models, and real-time communication using WebSocket is used for overall system coordination. 【0386】 Furthermore, feedback tailored to the user's emotions is reflected in the agent through an emotion analysis system that analyzes the user's psychological state in real time. This process is performed using natural language processing models such as Hugging Face Transformers. The system receives user feedback through a management system and uses it as data for evaluation and improvement. 【0387】 As a concrete example, in a video streaming application, if the system analyzes that a user is experiencing stress, the server will recommend enjoyable content. In this case, the generative AI model can be prompted with a prompt such as, "Suggest video genres that match the user's desired emotions," providing instructions for appropriate content recommendations. This system enables personalized responses tailored to each user's individual emotions. 【0388】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0389】 Step 1: 【0390】 The server collects business data from terminals in each business department. This includes transaction information from the sales department and work logs from the manufacturing department. The collected data is used as input by an information processing system and formatted into an appropriate format. The formatted business data is then output. 【0391】 Step 2: 【0392】 The server analyzes formatted business data using process mining techniques. It analyzes the data using Python and Pandas to identify business processes. Using formatted business data as input, it generates the identified business processes as output. Specifically, it performs data pattern recognition and statistical analysis. 【0393】 Step 3: 【0394】 The server generates an optimized process plan based on the identified business processes. It utilizes processing tools and AI models to perform calculations to optimize the processes. The input data is the identified business processes, and the output is the optimized process plan. The operation includes simulating and evaluating multiple process options. 【0395】 Step 4: 【0396】 The server deploys and operates general-purpose intelligent agents to each business process based on an optimized process plan. Using a configuration method, it communicates in real time via WebSocket and directs the agents to operate according to instructions. The input is the optimized process plan, and the output is the results of the agent's operation. Specifically, it initiates agents and sends commands. 【0397】 Step 5: 【0398】 The server analyzes the user's psychological state using emotion analysis tools. It uses natural language processing models such as Hugging Face Transformers to convert user voice and text data into emotion data. The input data is the user's communication log, and the output is the user's emotional state. Specifically, it performs voice analysis and text emotion analysis. 【0399】 Step 6: 【0400】 The server reflects the analyzed user's emotional state in the operation of the aforementioned agent. Using management tools, it generates responses adapted to the emotion and provides feedback to the agent. The input is the user's emotional state, and the output is the agent's response result. The prompt is "Generate a response that matches the emotion the user desires." The specific actions involve generating or modifying the response. 【0401】 Step 7: 【0402】 The user receives the agent's response and evaluates it. The server processes the evaluation results using management tools and uses them for continuous system improvement. The input data is the user's evaluation, and the output is the improved agent performance. Specific operations include collecting and analyzing feedback. 【0403】 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. 【0404】 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. 【0405】 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. 【0406】 [Third Embodiment] 【0407】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0408】 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. 【0409】 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). 【0410】 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. 【0411】 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. 【0412】 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). 【0413】 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. 【0414】 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. 【0415】 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. 【0416】 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. 【0417】 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. 【0418】 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". 【0419】 This invention is a system that utilizes artificial intelligence agents to streamline various business processes within a company. This system operates based on a series of programs designed to efficiently collect and analyze business data scattered throughout the company. 【0420】 Data collection and process mining 【0421】 The server collects business data from terminals in each business department. This data includes transaction information from the sales department, operational status from the manufacturing department, and inventory information. Based on the collected data, the server performs process mining to visualize the current state of business processes and identify bottlenecks. 【0422】 Plans for deploying artificial intelligence agents 【0423】 The server then devises an optimal agent deployment plan based on the results of process mining. For example, it might plan to deploy an AI customer support agent to the sales department, which is spending a lot of time on customer support. 【0424】 Agent deployment and management 【0425】 The terminal installs an artificial intelligence agent into the designated business process according to instructions received from the server. The agent has functions such as automatically responding to customer inquiries and improves business efficiency by operating autonomously. 【0426】 Agent operation and coordination 【0427】 Users utilize the agent's behavior in their daily tasks and evaluate its performance. The server adjusts the agent's behavior based on user feedback, improving and updating its functionality as needed. This continuous improvement process prevents the agent from becoming obsolete and ensures it always meets the latest business requirements. 【0428】 This system enables unified data utilization and efficient business processes across the entire company. 【0429】 The following describes the processing flow. 【0430】 Step 1: 【0431】 The server accesses ERP systems and CRM databases from various terminals within the company to collect business-related data. This data includes customer transaction history, manufacturing process information, and inventory status. 【0432】 Step 2: 【0433】 The server analyzes the collected data using process mining techniques. Specifically, it generates flowcharts of business processes from the data and identifies process bottlenecks by analyzing the time and frequency required for each process. 【0434】 Step 3: 【0435】 Based on the results of process mining, the server develops a plan for deploying the most suitable artificial intelligence agent for each business process. For example, if the sales department spends a long time dealing with customers, it plans to deploy a customer support agent. 【0436】 Step 4: 【0437】 The terminal, following instructions from the server, installs and starts operating an artificial intelligence agent for the specified business process. The agent is designed to support specific tasks, such as automated responses and inventory optimization. 【0438】 Step 5: 【0439】 Users utilize artificial intelligence agents in their work and evaluate their performance. Based on the agent's output, they can assess the degree of improvement in work efficiency. 【0440】 Step 6: 【0441】 The server collects feedback from users and adjusts the operation of the artificial intelligence agent. These adjustments include improving response accuracy and addressing new business requirements. 【0442】 Step 7: 【0443】 The server continuously undergoes functional improvements and updates to prevent the artificial intelligence agent from becoming obsolete. This process ensures that the system can always adapt to the business needs within the company. 【0444】 (Example 1) 【0445】 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." 【0446】 In recent years, business processes within companies have become increasingly complex, making their efficient management and optimization a critical challenge for many. Traditional methods lack a consistent system from the collection and analysis of business data to the deployment and operation of automated agents, and in particular, the continuous improvement and optimization of agents are not adequately carried out. This hinders the improvement of efficiency and the smooth operation of business processes. 【0447】 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. 【0448】 In this invention, the server includes information processing means for collecting business information, processing means for identifying business processes and generating optimized process plans by analyzing the collected business information, and deployment means for deploying and operating automated agents based on the process plan. This makes it possible to efficiently manage business processes within a company and achieve continuous process improvement and optimization. 【0449】 "Business information" refers to all data related to business processes within a company, including transaction information, manufacturing data, inventory status, etc. 【0450】 "Information processing means" refers to devices and software used to effectively collect business information and store it in a database. 【0451】 "Analysis methods" refer to methods and tools used to identify business processes and discover areas for improvement based on collected business information. 【0452】 "Processing means" refers to technologies and methods for generating plans to optimize business processes based on analyzed information. 【0453】 "Process planning" refers to the optimal procedures and strategies set out to streamline business processes. 【0454】 An "automation agent" is software or a system that autonomously handles specific tasks in a business process, and often utilizes artificial intelligence technology. 【0455】 "Deployment means" refers to the methods and technologies for introducing and operating automated agents into appropriate business processes based on process planning. 【0456】 "Control means" refers to methods and techniques for monitoring the operation of an automated agent and adjusting its operation based on feedback as needed. 【0457】 "Improvement measures" refer to technologies and methods for continuously improving and updating the functionality of automated agents. 【0458】 "Generative AI models" refer to technologies that use generative artificial intelligence techniques to build data-based models and propose the best options and strategies for business processes. 【0459】 A "prompt" refers to a series of instructions or questions entered by a user or system to operate a generative AI model. 【0460】 This invention relates to a system for effectively managing and optimizing business processes within a company. The system efficiently processes business information and utilizes automated agents to improve operational efficiency. 【0461】 The server uses database management systems such as MySQL and PostgreSQL to collect business information from each business department. This business information includes various types of information necessary for business operations, such as transaction information, manufacturing operation data, and inventory status. Based on the collected information, the server analyzes the data using process analysis techniques (e.g., process mining tools). 【0462】 Based on the analysis results, the server uses a generated AI model to create an optimized business process plan. Based on this plan, the server decides on the deployment of automated agents. For example, deploying a chatbot agent to the customer service department allows for faster responses to customer inquiries and reduces the workload. 【0463】 The terminal uses RPA tools and related software to install and configure agents based on instructions from the server. The agents operate autonomously on the terminal, ensuring smooth execution of business processes. Users evaluate the agent's performance in their daily work and provide feedback to the server. 【0464】 As a concrete example, in the sales department, the AI ​​agent significantly reduced customer response time, enabling them to handle twice as many customers in a single day. Based on this feedback, the server uses a generated AI model to adjust prompt messages and improve the agent's response accuracy. 【0465】 Examples of prompt messages include the following: 【0466】 "Please propose a plan to implement the optimal AI agent in our sales department to streamline the customer service process. Current data includes response time, customer satisfaction, and transaction volume." 【0467】 By using this system, companies can continuously improve their business processes and always meet the latest business requirements. 【0468】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0469】 Step 1: 【0470】 The server collects business information. It uses databases provided from terminals in each business department (e.g., transaction information, manufacturing operation data, inventory status) as input. The collected data is stored in a database management system and forms the basis for subsequent analysis. 【0471】 Step 2: 【0472】 The server analyzes the collected data using process analysis techniques. It uses process mining tools to perform the analysis and identify business processes. The input is business information stored in a database, and the output provides visualization of business processes and identification of bottlenecks. 【0473】 Step 3: 【0474】 The server uses the generated AI model to generate an optimized business process plan. Using the analysis results from step 2 as input, it obtains the optimal process placement proposed by the generated AI model as output. This plan is used to deploy the automation agents. 【0475】 Step 4: 【0476】 The terminal deploys automation agents to specified business processes based on instructions from the server. The input is a business process plan, and the output is an environment where agents are correctly installed and operational. Specifically, RPA tools are used on the terminal to configure and start the agents. 【0477】 Step 5: 【0478】 Users utilize agents in their daily work and evaluate their performance. Inputs include data on agent operation results and work efficiency, while output is feedback that is sent to the server. This feedback is used to determine areas for improvement and the effectiveness of the agents. 【0479】 Step 6: 【0480】 The server retrains the generated AI model and adjusts the agent's behavior based on user feedback. Using feedback data as input, the AI ​​model outputs improved prompts and adjusted agent behavior. This process ensures that the agent is always operating in an optimal state, adapted to business requirements. 【0481】 (Application Example 1) 【0482】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0483】 In modern manufacturing, identifying and resolving bottlenecks in complex production processes is crucial. Traditional methods suffer from inefficient data collection and analysis, making real-time situational awareness difficult. Furthermore, the operation of artificial intelligence agents presents challenges, such as the difficulty of continuous improvement and the tendency for their performance to become obsolete. 【0484】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0485】 In this invention, the server includes data processing means for collecting business information, calculation means for identifying business procedures and generating an optimized procedure plan by analyzing the collected business information, and visualization means for monitoring the status of factory operations in real time and identifying bottlenecks. This enables efficient optimization of the manufacturing process and effective operation of artificial intelligence agents. 【0486】 "Business information" is a general term for information such as transaction information, manufacturing status, and inventory information obtained from various business processes carried out within a company. 【0487】 "Data processing means" refers to a series of technical methods and devices for collecting, appropriately storing, and managing business information. 【0488】 "Business procedures" refer to the established procedures, processes, and workflows within a company, contributing to the efficient operation of the business. 【0489】 "Computation means" refers to a device or technology that analyzes collected business information and performs processing to generate an optimal procedure plan. 【0490】 A "procedure plan" is a plan or strategy devised to optimize specific work procedures. 【0491】 "Visualization means" refers to technologies or devices that visually display the progress and status of factory operations in real time, and that clearly identify bottlenecks. 【0492】 A "bottleneck" refers to a specific part or factor in a business process that causes delays or reduced efficiency. 【0493】 "Management and control means" refers to management systems and technologies for monitoring the operation of artificial intelligence agents and making adjustments as needed. 【0494】 This invention relates to a system aimed at improving the efficiency of business processes in a manufacturing environment. The server collects business information generated within the factory through sensors and terminals. This information includes the operating status of the production line, equipment usage data, inventory information, and so on. 【0495】 The server processes and analyzes the collected data using data analysis tools such as Python. The analysis results identify business procedures through process mining techniques, generating optimized procedure plans. By using process mining software such as Celonis, the manufacturing process can be visualized, making it easier to identify bottlenecks. 【0496】 The visualization results are displayed on the device via visualization tools such as Tableau. This allows users to monitor the situation on the manufacturing floor in real time and respond immediately if an anomaly occurs. 【0497】 Furthermore, artificial intelligence agents are strategically deployed to automate business processes. Through management and control mechanisms, agent behavior is continuously monitored and adjusted, and alerts can be sent to users using notification functions such as Twilio. 【0498】 For example, if a delay in material supply is detected on a particular manufacturing line, the server immediately sends out a notification and proposes relocating the material supply agent as a countermeasure. If the user implements this improvement appropriately, it will enhance the overall efficiency of the manufacturing process. 【0499】 By utilizing a generative AI model, and using an example prompt such as, "Analyze the data from this factory's production line and visualize the causes of delays and solutions using process mining," efficient system operation becomes possible. 【0500】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0501】 Step 1: 【0502】 The server collects operational information from sensors and terminals within the factory. Input data includes manufacturing line operating status, equipment usage data, and inventory information. This data is converted into a specific format and stored in a database suitable for analysis. 【0503】 Step 2: 【0504】 The server processes the collected data using Python data analysis libraries (such as Pandas and NumPy). Specifically, it performs data imputation and removal of outliers to generate a clean dataset. This clean data is then used for subsequent process mining. 【0505】 Step 3: 【0506】 The server uses process mining techniques to identify business procedures from clean data and generate an optimized procedure plan. This process utilizes process mining tools like Celonis to visualize the flow and bottlenecks of business procedures. The output is an optimized procedure plan. 【0507】 Step 4: 【0508】 The server deploys artificial intelligence agents based on the generated procedure plan and initiates the automated process. During this process, the agents' operation is optimized, focusing on bottlenecks identified in the plan to ensure efficient operation. The agents autonomously perform their scheduled tasks and provide progress information to the server. 【0509】 Step 5: 【0510】 The terminal uses visualization tools such as Tableau to display the generated procedure plan and agent operation status in real time. Based on this visualized information, users can understand the current situation on the manufacturing floor and take immediate action if any abnormalities are detected. 【0511】 Step 6: 【0512】 The server continuously monitors the agent's operation using management and control mechanisms and makes adjustments as needed. Specifically, it receives user feedback and abnormal data, and uses AI models to improve the agent's operation. It also sends alerts to users using notification functions such as Twilio. 【0513】 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. 【0514】 This invention provides an artificial intelligence agent system for optimizing and autonomously operating business processes within a company, and further enhances the system's responsiveness and adaptability by incorporating an emotion engine that recognizes user emotions. 【0515】 Data collection and process mining 【0516】 The server collects business data from terminals in each business department. This data includes transaction information from the sales department and logs related to the manufacturing process from the manufacturing department, and the server analyzes this data using process mining techniques. Based on the analysis results, it identifies business processes and generates an optimal process plan. 【0517】 Introduction of artificial intelligence agents 【0518】 The server deploys artificial intelligence agents based on the process plan and begins operations in each process. For example, in customer support, agents are used to respond quickly to user inquiries. 【0519】 Emotional engine integration 【0520】 Furthermore, by incorporating an emotion engine into this system, the system can recognize the user's emotional state and feed that data back into the agent's response. For example, if the emotion engine determines that the user is stressed, the information and responses provided by the agent can be changed. 【0521】 Feedback and Improvement 【0522】 Users can evaluate the agent's output and emotional responses in their work. The server adjusts the agent's behavior and emotion engine settings based on this feedback. This continuous improvement process ensures that the system always adapts to user needs and prevents agent obsolescence. 【0523】 This configuration makes it possible to achieve efficient business processes while taking user emotions into consideration, thereby supporting improved productivity across the entire company. 【0524】 The following describes the processing flow. 【0525】 Step 1: 【0526】 The server collects necessary business data from each terminal within the company through ERP systems and CRM databases. This data includes customer transaction history, inventory status, and manufacturing process logs. 【0527】 Step 2: 【0528】 The server analyzes the collected business data using process mining algorithms to identify each business process and evaluate its efficiency. Based on the analysis results, it generates a process plan to improve bottleneck processes. 【0529】 Step 3: 【0530】 Based on the generated process plan, the server selects the most suitable artificial intelligence agent for each business process and instructs the terminal to install it. This agent is responsible for streamlining tasks such as customer support inquiries and manufacturing inventory management. 【0531】 Step 4: 【0532】 The terminal, following instructions from the server, installs agents in the specified order of business processes and begins operation. The agents continuously execute algorithms to optimize operations and autonomously continue tasks that were initially configured for their specific roles. 【0533】 Step 5: 【0534】 The user interacts with the operational artificial intelligence agent to check the progress of their tasks. The emotion engine analyzes the user's emotions in real time, and if, for example, the user is feeling stressed, the agent's response is flexibly adjusted accordingly. 【0535】 Step 6: 【0536】 The server collects feedback from user experience and sentiment analysis, and updates the settings of the artificial intelligence agent and emotion engine. This feedback loop allows each agent to be continuously improved, leading to enhanced agent performance and a higher quality user experience. 【0537】 Step 7: 【0538】 The server combines the analysis results from the emotion engine with business data to formulate and implement a company-wide process optimization strategy. This strategy aims to improve efficiency across the entire enterprise, and as needed, it involves large-scale updates and expansions of agents and processes. 【0539】 (Example 2) 【0540】 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." 【0541】 While there is a demand for increased efficiency in business processes, a challenge remains in ensuring that agents respond appropriately to users' emotions and improve the flexibility and usability of those processes. To achieve this, a proper understanding of business procedures, the creation of optimized plans, and the autonomous operation of intelligent programs are essential. 【0542】 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. 【0543】 In this invention, the server includes data acquisition means for collecting business information, information analysis means for analyzing the acquired business information, identifying business procedures, and generating an optimized procedure plan, and deployment means for deploying and operating intelligent programs to each business procedure based on the procedure plan. This enables more efficient and flexible operation of business processes. 【0544】 "Data acquisition means" refers to technology equipped with functions for effectively collecting and processing business information. 【0545】 "Information analysis means" refers to technologies for analyzing collected business information, identifying business procedures, and generating optimized plans. 【0546】 A "deployment mechanism" is a mechanism for deploying and operating an intelligent program at each step of a business procedure based on the generated procedure plan. 【0547】 "Emotion recognition function" is a technology that detects the user's emotional state and reflects it in the response of the intelligent program. 【0548】 "Control means" refers to the technology that manages the process of monitoring the operation of an intelligent program and adjusting settings and parameters based on feedback. 【0549】 This invention is a system for autonomously optimizing and operating a company's business processes. Its embodiments are described in detail below. 【0550】 First, the server collects business information from terminals in each business department within the company. This information collection uses a communication protocol to send the information to a database via a network connection. The information collected includes data such as transaction history from the sales department and process data from the manufacturing department. 【0551】 Next, the server analyzes the collected information using "information analysis tools." At this stage, general business process analysis software is used, for example, utilizing open-source process mining tools to visualize business procedures and generate optimized plans. 【0552】 In each business process, the server deploys artificial intelligence agents using a "deployment method." These agents are typically implemented using cloud-based AI services and are configured specifically to interact with users using natural language processing. In this process, the system utilizes a generative AI model to provide quick and appropriate responses based on user input. 【0553】 Furthermore, the server integrates "emotion recognition functionality" into the agent, allowing it to determine the user's emotional state and reflect it in its response. For example, it can adjust the tone and content of the response to provide a better user experience. 【0554】 Finally, the system continuously collects user feedback and adjusts its intelligent program using "control mechanisms." This ensures that the system is always adaptable to the latest business requirements and enables continuous improvement of business processes. 【0555】 As a concrete example, consider a customer support scenario. When a user enters a prompt such as, "To improve customer support operations, please explain how agents determine a user's emotions and provide diverse responses," the system can then provide the user with the most appropriate information and procedures based on that input. 【0556】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0557】 Step 1: 【0558】 The server collects business information from business terminals. This information collection automatically retrieves transaction data, process logs, and other data from terminals in each department via the network. The input is business data transmitted from the terminals, and the output is an integrated database stored on the server. This allows for the aggregation of business information across the entire company. 【0559】 Step 2: 【0560】 The server analyzes the collected business information using "information analysis tools." Specifically, it uses open-source process mining software to identify business procedures. The input is business information stored in an integrated database, and the output is the analyzed process flow and optimized business plan. This reveals inefficiencies in the current process. 【0561】 Step 3: 【0562】 The server deploys artificial intelligence agents based on an optimized work plan. Deployment utilizes cloud-based AI services and loads natural language processing models to enable user interaction. The input is the optimized work plan, and the output is the agent setup status adapted to each work step. This allows the agents to begin handling the work. 【0563】 Step 4: 【0564】 The server integrates "emotion recognition functionality" into the agent, adjusting its response according to the user's emotions. Specifically, it uses an emotion analysis tool to analyze the user's input text. The input is the user's inquiry or feedback, and the output is the analyzed emotional state. Based on this, the agent takes the most appropriate action for the user. 【0565】 Step 5: 【0566】 Users evaluate the agent's service quality and provide feedback. This feedback is sent to the server, which then adjusts the agent's response patterns and sentiment settings based on it. The input is user evaluation data, and the output is the improved agent response settings. This allows for continuous improvement of service quality. 【0567】 (Application Example 2) 【0568】 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." 【0569】 This invention aims to improve both operational efficiency and user satisfaction simultaneously by enabling appropriate responses that respond to user emotions in business processes within companies. Conventional systems often fail to adequately consider user emotions, resulting in a decline in the quality of business processes and responses. The challenge lies in resolving this issue and achieving more adaptive and effective business operations. 【0570】 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. 【0571】 In this invention, the server includes information processing means for collecting business data; processing means for identifying business processes and generating optimized process plans by analyzing the collected business data; configuration means for deploying and operating general-purpose intelligent agents for each business process based on the process plan; management means for monitoring the operation of the general-purpose intelligent agents and adjusting them based on feedback; and emotion analysis means for analyzing the user's psychological state and reflecting that information in the responses of the general-purpose intelligent agents. This enables appropriate optimization of business processes and personalized responses that take into account the user's emotions. 【0572】 "Information processing means" refers to a device or method that collects and analyzes business data to support the identification and optimization of business processes. 【0573】 "Processing means" refers to an apparatus or method for analyzing collected business data to identify business processes and generate an optimized process plan. 【0574】 "Configuration means" refers to a device or method that deploys general-purpose intelligent agents to each business process and executes operations based on an optimized process plan. 【0575】 "Management means" refers to a device or method for monitoring the operation of a general-purpose intelligent agent and adjusting the agent's operation based on feedback. 【0576】 "Emotional analysis means" refers to a device or method that analyzes the psychological state of a user and uses that information to adapt the response of a general-purpose intelligent agent. 【0577】 As a means of implementing this invention, a system that utilizes the technology infrastructure within a company is proposed. The server uses information processing means to collect business data from terminals in each business department. The collected data includes transaction information from sales and work logs from the manufacturing department. This data is analyzed by data analysis software using Python or Pandas, business processes are identified using process mining techniques, and an optimized process plan is generated. 【0578】 Based on the generated process plan, the server deploys general-purpose intelligent agents to each business process and begins operation using configuration methods. This involves agents using AI models, and real-time communication using WebSocket is used for overall system coordination. 【0579】 Furthermore, feedback tailored to the user's emotions is reflected in the agent through an emotion analysis system that analyzes the user's psychological state in real time. This process is performed using natural language processing models such as Hugging Face Transformers. The system receives user feedback through a management system and uses it as data for evaluation and improvement. 【0580】 As a concrete example, in a video streaming application, if the system analyzes that a user is experiencing stress, the server will recommend enjoyable content. In this case, the generative AI model can be prompted with a prompt such as, "Suggest video genres that match the user's desired emotions," providing instructions for appropriate content recommendations. This system enables personalized responses tailored to each user's individual emotions. 【0581】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0582】 Step 1: 【0583】 The server collects business data from terminals in each business department. This includes transaction information from the sales department and work logs from the manufacturing department. The collected data is used as input by an information processing system and formatted into an appropriate format. The formatted business data is then output. 【0584】 Step 2: 【0585】 The server analyzes formatted business data using process mining techniques. It analyzes the data using Python and Pandas to identify business processes. Using formatted business data as input, it generates the identified business processes as output. Specifically, it performs data pattern recognition and statistical analysis. 【0586】 Step 3: 【0587】 The server generates an optimized process plan based on the identified business processes. It utilizes processing tools and AI models to perform calculations to optimize the processes. The input data is the identified business processes, and the output is the optimized process plan. The operation includes simulating and evaluating multiple process options. 【0588】 Step 4: 【0589】 The server deploys and operates general-purpose intelligent agents to each business process based on an optimized process plan. Using a configuration method, it communicates in real time via WebSocket and directs the agents to operate according to instructions. The input is the optimized process plan, and the output is the results of the agent's operation. Specifically, it initiates agents and sends commands. 【0590】 Step 5: 【0591】 The server analyzes the user's psychological state using emotion analysis tools. It uses natural language processing models such as Hugging Face Transformers to convert user voice and text data into emotion data. The input data is the user's communication log, and the output is the user's emotional state. Specifically, it performs voice analysis and text emotion analysis. 【0592】 Step 6: 【0593】 The server reflects the analyzed user's emotional state in the operation of the aforementioned agent. Using management tools, it generates responses adapted to the emotion and provides feedback to the agent. The input is the user's emotional state, and the output is the agent's response result. The prompt is "Generate a response that matches the emotion the user desires." The specific actions involve generating or modifying the response. 【0594】 Step 7: 【0595】 The user receives the agent's response and evaluates it. The server processes the evaluation results using management tools and uses them for continuous system improvement. The input data is the user's evaluation, and the output is the improved agent performance. Specific operations include collecting and analyzing feedback. 【0596】 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. 【0597】 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. 【0598】 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. 【0599】 [Fourth Embodiment] 【0600】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0601】 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. 【0602】 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). 【0603】 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. 【0604】 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. 【0605】 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). 【0606】 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. 【0607】 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. 【0608】 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. 【0609】 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. 【0610】 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. 【0611】 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. 【0612】 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". 【0613】 This invention is a system that utilizes artificial intelligence agents to streamline various business processes within a company. This system operates based on a series of programs designed to efficiently collect and analyze business data scattered throughout the company. 【0614】 Data collection and process mining 【0615】 The server collects business data from terminals in each business department. This data includes transaction information from the sales department, operational status from the manufacturing department, and inventory information. Based on the collected data, the server performs process mining to visualize the current state of business processes and identify bottlenecks. 【0616】 Plans for deploying artificial intelligence agents 【0617】 The server then devises an optimal agent deployment plan based on the results of process mining. For example, it might plan to deploy an AI customer support agent to the sales department, which is spending a lot of time on customer support. 【0618】 Agent deployment and management 【0619】 The terminal installs an artificial intelligence agent into the designated business process according to instructions received from the server. The agent has functions such as automatically responding to customer inquiries and improves business efficiency by operating autonomously. 【0620】 Agent operation and coordination 【0621】 Users utilize the agent's behavior in their daily tasks and evaluate its performance. The server adjusts the agent's behavior based on user feedback, improving and updating its functionality as needed. This continuous improvement process prevents the agent from becoming obsolete and ensures it always meets the latest business requirements. 【0622】 This system enables unified data utilization and efficient business processes across the entire company. 【0623】 The following describes the processing flow. 【0624】 Step 1: 【0625】 The server accesses ERP systems and CRM databases from various terminals within the company to collect business-related data. This data includes customer transaction history, manufacturing process information, and inventory status. 【0626】 Step 2: 【0627】 The server analyzes the collected data using process mining techniques. Specifically, it generates flowcharts of business processes from the data and identifies process bottlenecks by analyzing the time and frequency required for each process. 【0628】 Step 3: 【0629】 Based on the results of process mining, the server develops a plan for deploying the most suitable artificial intelligence agent for each business process. For example, if the sales department spends a long time dealing with customers, it plans to deploy a customer support agent. 【0630】 Step 4: 【0631】 The terminal, following instructions from the server, installs and starts operating an artificial intelligence agent for the specified business process. The agent is designed to support specific tasks, such as automated responses and inventory optimization. 【0632】 Step 5: 【0633】 Users utilize artificial intelligence agents in their work and evaluate their performance. Based on the agent's output, they can assess the degree of improvement in work efficiency. 【0634】 Step 6: 【0635】 The server collects feedback from users and adjusts the operation of the artificial intelligence agent. These adjustments include improving response accuracy and addressing new business requirements. 【0636】 Step 7: 【0637】 The server continuously undergoes functional improvements and updates to prevent the artificial intelligence agent from becoming obsolete. This process ensures that the system can always adapt to the business needs within the company. 【0638】 (Example 1) 【0639】 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". 【0640】 In recent years, business processes within companies have become increasingly complex, making their efficient management and optimization a critical challenge for many. Traditional methods lack a consistent system from the collection and analysis of business data to the deployment and operation of automated agents, and in particular, the continuous improvement and optimization of agents are not adequately carried out. This hinders the improvement of efficiency and the smooth operation of business processes. 【0641】 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. 【0642】 In this invention, the server includes information processing means for collecting business information, processing means for identifying business processes and generating optimized process plans by analyzing the collected business information, and deployment means for deploying and operating automated agents based on the process plan. This makes it possible to efficiently manage business processes within a company and achieve continuous process improvement and optimization. 【0643】 "Business information" refers to all data related to business processes within a company, including transaction information, manufacturing data, inventory status, etc. 【0644】 "Information processing means" refers to devices and software used to effectively collect business information and store it in a database. 【0645】 "Analysis methods" refer to methods and tools used to identify business processes and discover areas for improvement based on collected business information. 【0646】 "Processing means" refers to technologies and methods for generating plans to optimize business processes based on analyzed information. 【0647】 "Process planning" refers to the optimal procedures and strategies set out to streamline business processes. 【0648】 An "automation agent" is software or a system that autonomously handles specific tasks in a business process, and often utilizes artificial intelligence technology. 【0649】 "Deployment means" refers to the methods and technologies for introducing and operating automated agents into appropriate business processes based on process planning. 【0650】 "Control means" refers to methods and techniques for monitoring the operation of an automated agent and adjusting its operation based on feedback as needed. 【0651】 "Improvement measures" refer to technologies and methods for continuously improving and updating the functionality of automated agents. 【0652】 "Generative AI models" refer to technologies that use generative artificial intelligence techniques to build data-based models and propose the best options and strategies for business processes. 【0653】 A "prompt" refers to a series of instructions or questions entered by a user or system to operate a generative AI model. 【0654】 This invention relates to a system for effectively managing and optimizing business processes within a company. The system efficiently processes business information and utilizes automated agents to improve operational efficiency. 【0655】 The server uses database management systems such as MySQL and PostgreSQL to collect business information from each business department. This business information includes various types of information necessary for business operations, such as transaction information, manufacturing operation data, and inventory status. Based on the collected information, the server analyzes the data using process analysis techniques (e.g., process mining tools). 【0656】 Based on the analysis results, the server uses a generated AI model to create an optimized business process plan. Based on this plan, the server decides on the deployment of automated agents. For example, deploying a chatbot agent to the customer service department allows for faster responses to customer inquiries and reduces the workload. 【0657】 The terminal uses RPA tools and related software to install and configure agents based on instructions from the server. The agents operate autonomously on the terminal, ensuring smooth execution of business processes. Users evaluate the agent's performance in their daily work and provide feedback to the server. 【0658】 As a concrete example, in the sales department, the AI ​​agent significantly reduced customer response time, enabling them to handle twice as many customers in a single day. Based on this feedback, the server uses a generated AI model to adjust prompt messages and improve the agent's response accuracy. 【0659】 Examples of prompt messages include the following: 【0660】 "Please propose a plan to implement the optimal AI agent in our sales department to streamline the customer service process. Current data includes response time, customer satisfaction, and transaction volume." 【0661】 By using this system, companies can continuously improve their business processes and always meet the latest business requirements. 【0662】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0663】 Step 1: 【0664】 The server collects business information. It uses databases provided from terminals in each business department (e.g., transaction information, manufacturing operation data, inventory status) as input. The collected data is stored in a database management system and forms the basis for subsequent analysis. 【0665】 Step 2: 【0666】 The server analyzes the collected data using process analysis techniques. It uses process mining tools to perform the analysis and identify business processes. The input is business information stored in a database, and the output provides visualization of business processes and identification of bottlenecks. 【0667】 Step 3: 【0668】 The server uses the generated AI model to generate an optimized business process plan. Using the analysis results from step 2 as input, it obtains the optimal process placement proposed by the generated AI model as output. This plan is used to deploy the automation agents. 【0669】 Step 4: 【0670】 The terminal deploys automation agents to specified business processes based on instructions from the server. The input is a business process plan, and the output is an environment where agents are correctly installed and operational. Specifically, RPA tools are used on the terminal to configure and start the agents. 【0671】 Step 5: 【0672】 Users utilize agents in their daily work and evaluate their performance. Inputs include data on agent operation results and work efficiency, while output is feedback that is sent to the server. This feedback is used to determine areas for improvement and the effectiveness of the agents. 【0673】 Step 6: 【0674】 The server retrains the generated AI model and adjusts the agent's behavior based on user feedback. Using feedback data as input, the AI ​​model outputs improved prompts and adjusted agent behavior. This process ensures that the agent is always operating in an optimal state, adapted to business requirements. 【0675】 (Application Example 1) 【0676】 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". 【0677】 In modern manufacturing, identifying and resolving bottlenecks in complex production processes is crucial. Traditional methods suffer from inefficient data collection and analysis, making real-time situational awareness difficult. Furthermore, the operation of artificial intelligence agents presents challenges, such as the difficulty of continuous improvement and the tendency for their performance to become obsolete. 【0678】 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. 【0679】 In this invention, the server includes data processing means for collecting business information, calculation means for identifying business procedures and generating an optimized procedure plan by analyzing the collected business information, and visualization means for monitoring the status of factory operations in real time and identifying bottlenecks. This enables efficient optimization of the manufacturing process and effective operation of artificial intelligence agents. 【0680】 "Business information" is a general term for information such as transaction information, manufacturing status, and inventory information obtained from various business processes carried out within a company. 【0681】 "Data processing means" refers to a series of technical methods and devices for collecting, appropriately storing, and managing business information. 【0682】 "Business procedures" refer to the established procedures, processes, and workflows within a company, contributing to the efficient operation of the business. 【0683】 "Computation means" refers to a device or technology that analyzes collected business information and performs processing to generate an optimal procedure plan. 【0684】 A "procedure plan" is a plan or strategy devised to optimize specific work procedures. 【0685】 "Visualization means" refers to technologies or devices that visually display the progress and status of factory operations in real time, and that clearly identify bottlenecks. 【0686】 A "bottleneck" refers to a specific part or factor in a business process that causes delays or reduced efficiency. 【0687】 "Management and control means" refers to management systems and technologies for monitoring the operation of artificial intelligence agents and making adjustments as needed. 【0688】 This invention relates to a system aimed at improving the efficiency of business processes in a manufacturing environment. The server collects business information generated within the factory through sensors and terminals. This information includes the operating status of the production line, equipment usage data, inventory information, and so on. 【0689】 The server processes and analyzes the collected data using data analysis tools such as Python. The analysis results identify business procedures through process mining techniques, generating optimized procedure plans. By using process mining software such as Celonis, the manufacturing process can be visualized, making it easier to identify bottlenecks. 【0690】 The visualization results are displayed on the device via visualization tools such as Tableau. This allows users to monitor the situation on the manufacturing floor in real time and respond immediately if an anomaly occurs. 【0691】 Furthermore, artificial intelligence agents are strategically deployed to automate business processes. Through management and control mechanisms, agent behavior is continuously monitored and adjusted, and alerts can be sent to users using notification functions such as Twilio. 【0692】 For example, if a delay in material supply is detected on a particular manufacturing line, the server immediately sends out a notification and proposes relocating the material supply agent as a countermeasure. If the user implements this improvement appropriately, it will enhance the overall efficiency of the manufacturing process. 【0693】 By utilizing a generative AI model, and using an example prompt such as, "Analyze the data from this factory's production line and visualize the causes of delays and solutions using process mining," efficient system operation becomes possible. 【0694】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0695】 Step 1: 【0696】 The server collects operational information from sensors and terminals within the factory. Input data includes manufacturing line operating status, equipment usage data, and inventory information. This data is converted into a specific format and stored in a database suitable for analysis. 【0697】 Step 2: 【0698】 The server processes the collected data using Python data analysis libraries (such as Pandas and NumPy). Specifically, it performs data imputation and removal of outliers to generate a clean dataset. This clean data is then used for subsequent process mining. 【0699】 Step 3: 【0700】 The server uses process mining techniques to identify business procedures from clean data and generate an optimized procedure plan. This process utilizes process mining tools like Celonis to visualize the flow and bottlenecks of business procedures. The output is an optimized procedure plan. 【0701】 Step 4: 【0702】 The server deploys artificial intelligence agents based on the generated procedure plan and initiates the automated process. During this process, the agents' operation is optimized, focusing on bottlenecks identified in the plan to ensure efficient operation. The agents autonomously perform their scheduled tasks and provide progress information to the server. 【0703】 Step 5: 【0704】 The terminal uses visualization tools such as Tableau to display the generated procedure plan and agent operation status in real time. Based on this visualized information, users can understand the current situation on the manufacturing floor and take immediate action if any abnormalities are detected. 【0705】 Step 6: 【0706】 The server continuously monitors the agent's operation using management and control mechanisms and makes adjustments as needed. Specifically, it receives user feedback and abnormal data, and uses AI models to improve the agent's operation. It also sends alerts to users using notification functions such as Twilio. 【0707】 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. 【0708】 This invention provides an artificial intelligence agent system for optimizing and autonomously operating business processes within a company, and further enhances the system's responsiveness and adaptability by incorporating an emotion engine that recognizes user emotions. 【0709】 Data collection and process mining 【0710】 The server collects business data from terminals in each business department. This data includes transaction information from the sales department and logs related to the manufacturing process from the manufacturing department, and the server analyzes this data using process mining techniques. Based on the analysis results, it identifies business processes and generates an optimal process plan. 【0711】 Introduction of artificial intelligence agents 【0712】 The server deploys artificial intelligence agents based on the process plan and begins operations in each process. For example, in customer support, agents are used to respond quickly to user inquiries. 【0713】 Emotional engine integration 【0714】 Furthermore, by incorporating an emotion engine into this system, the system can recognize the user's emotional state and feed that data back into the agent's response. For example, if the emotion engine determines that the user is stressed, the information and responses provided by the agent can be changed. 【0715】 Feedback and Improvement 【0716】 Users can evaluate the agent's output and emotional responses in their work. The server adjusts the agent's behavior and emotion engine settings based on this feedback. This continuous improvement process ensures that the system always adapts to user needs and prevents agent obsolescence. 【0717】 This configuration makes it possible to achieve efficient business processes while taking user emotions into consideration, thereby supporting improved productivity across the entire company. 【0718】 The following describes the processing flow. 【0719】 Step 1: 【0720】 The server collects necessary business data from each terminal within the company through ERP systems and CRM databases. This data includes customer transaction history, inventory status, and manufacturing process logs. 【0721】 Step 2: 【0722】 The server analyzes the collected business data using process mining algorithms to identify each business process and evaluate its efficiency. Based on the analysis results, it generates a process plan to improve bottleneck processes. 【0723】 Step 3: 【0724】 Based on the generated process plan, the server selects the most suitable artificial intelligence agent for each business process and instructs the terminal to install it. This agent is responsible for streamlining tasks such as customer support inquiries and manufacturing inventory management. 【0725】 Step 4: 【0726】 The terminal, following instructions from the server, installs agents in the specified order of business processes and begins operation. The agents continuously execute algorithms to optimize operations and autonomously continue tasks that were initially configured for their specific roles. 【0727】 Step 5: 【0728】 The user interacts with the operational artificial intelligence agent to check the progress of their tasks. The emotion engine analyzes the user's emotions in real time, and if, for example, the user is feeling stressed, the agent's response is flexibly adjusted accordingly. 【0729】 Step 6: 【0730】 The server collects feedback from user experience and sentiment analysis, and updates the settings of the artificial intelligence agent and emotion engine. This feedback loop allows each agent to be continuously improved, leading to enhanced agent performance and a higher quality user experience. 【0731】 Step 7: 【0732】 The server combines the analysis results from the emotion engine with business data to formulate and implement a company-wide process optimization strategy. This strategy aims to improve efficiency across the entire enterprise, and as needed, it involves large-scale updates and expansions of agents and processes. 【0733】 (Example 2) 【0734】 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". 【0735】 While there is a demand for increased efficiency in business processes, a challenge remains in ensuring that agents respond appropriately to users' emotions and improve the flexibility and usability of those processes. To achieve this, a proper understanding of business procedures, the creation of optimized plans, and the autonomous operation of intelligent programs are essential. 【0736】 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. 【0737】 In this invention, the server includes data acquisition means for collecting business information, information analysis means for analyzing the acquired business information, identifying business procedures, and generating an optimized procedure plan, and deployment means for deploying and operating intelligent programs to each business procedure based on the procedure plan. This enables more efficient and flexible operation of business processes. 【0738】 "Data acquisition means" refers to technology equipped with functions for effectively collecting and processing business information. 【0739】 "Information analysis means" refers to technologies for analyzing collected business information, identifying business procedures, and generating optimized plans. 【0740】 A "deployment mechanism" is a mechanism for deploying and operating an intelligent program at each step of a business procedure based on the generated procedure plan. 【0741】 "Emotion recognition function" is a technology that detects the user's emotional state and reflects it in the response of the intelligent program. 【0742】 "Control means" refers to the technology that manages the process of monitoring the operation of an intelligent program and adjusting settings and parameters based on feedback. 【0743】 This invention is a system for autonomously optimizing and operating a company's business processes. Its embodiments are described in detail below. 【0744】 First, the server collects business information from terminals in each business department within the company. This information collection uses a communication protocol to send the information to a database via a network connection. The information collected includes data such as transaction history from the sales department and process data from the manufacturing department. 【0745】 Next, the server analyzes the collected information using "information analysis tools." At this stage, general business process analysis software is used, for example, utilizing open-source process mining tools to visualize business procedures and generate optimized plans. 【0746】 In each business process, the server deploys artificial intelligence agents using a "deployment method." These agents are typically implemented using cloud-based AI services and are configured specifically to interact with users using natural language processing. In this process, the system utilizes a generative AI model to provide quick and appropriate responses based on user input. 【0747】 Furthermore, the server integrates "emotion recognition functionality" into the agent, allowing it to determine the user's emotional state and reflect it in its response. For example, it can adjust the tone and content of the response to provide a better user experience. 【0748】 Finally, the system continuously collects user feedback and adjusts its intelligent program using "control mechanisms." This ensures that the system is always adaptable to the latest business requirements and enables continuous improvement of business processes. 【0749】 As a concrete example, consider a customer support scenario. When a user enters a prompt such as, "To improve customer support operations, please explain how agents determine a user's emotions and provide diverse responses," the system can then provide the user with the most appropriate information and procedures based on that input. 【0750】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0751】 Step 1: 【0752】 The server collects business information from business terminals. This information collection automatically retrieves transaction data, process logs, and other data from terminals in each department via the network. The input is business data transmitted from the terminals, and the output is an integrated database stored on the server. This allows for the aggregation of business information across the entire company. 【0753】 Step 2: 【0754】 The server analyzes the collected business information using "information analysis tools." Specifically, it uses open-source process mining software to identify business procedures. The input is business information stored in an integrated database, and the output is the analyzed process flow and optimized business plan. This reveals inefficiencies in the current process. 【0755】 Step 3: 【0756】 The server deploys artificial intelligence agents based on an optimized work plan. Deployment utilizes cloud-based AI services and loads natural language processing models to enable user interaction. The input is the optimized work plan, and the output is the agent setup status adapted to each work step. This allows the agents to begin handling the work. 【0757】 Step 4: 【0758】 The server integrates "emotion recognition functionality" into the agent, adjusting its response according to the user's emotions. Specifically, it uses an emotion analysis tool to analyze the user's input text. The input is the user's inquiry or feedback, and the output is the analyzed emotional state. Based on this, the agent takes the most appropriate action for the user. 【0759】 Step 5: 【0760】 Users evaluate the agent's service quality and provide feedback. This feedback is sent to the server, which then adjusts the agent's response patterns and sentiment settings based on it. The input is user evaluation data, and the output is the improved agent response settings. This allows for continuous improvement of service quality. 【0761】 (Application Example 2) 【0762】 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". 【0763】 This invention aims to improve both operational efficiency and user satisfaction simultaneously by enabling appropriate responses that respond to user emotions in business processes within companies. Conventional systems often fail to adequately consider user emotions, resulting in a decline in the quality of business processes and responses. The challenge lies in resolving this issue and achieving more adaptive and effective business operations. 【0764】 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. 【0765】 In this invention, the server includes information processing means for collecting business data; processing means for identifying business processes and generating optimized process plans by analyzing the collected business data; configuration means for deploying and operating general-purpose intelligent agents for each business process based on the process plan; management means for monitoring the operation of the general-purpose intelligent agents and adjusting them based on feedback; and emotion analysis means for analyzing the user's psychological state and reflecting that information in the responses of the general-purpose intelligent agents. This enables appropriate optimization of business processes and personalized responses that take into account the user's emotions. 【0766】 "Information processing means" refers to a device or method that collects and analyzes business data to support the identification and optimization of business processes. 【0767】 "Processing means" refers to an apparatus or method for analyzing collected business data to identify business processes and generate an optimized process plan. 【0768】 "Configuration means" refers to a device or method that deploys general-purpose intelligent agents to each business process and executes operations based on an optimized process plan. 【0769】 "Management means" refers to a device or method for monitoring the operation of a general-purpose intelligent agent and adjusting the agent's operation based on feedback. 【0770】 "Emotional analysis means" refers to a device or method that analyzes the psychological state of a user and uses that information to adapt the response of a general-purpose intelligent agent. 【0771】 As a means of implementing this invention, a system that utilizes the technology infrastructure within a company is proposed. The server uses information processing means to collect business data from terminals in each business department. The collected data includes transaction information from sales and work logs from the manufacturing department. This data is analyzed by data analysis software using Python or Pandas, business processes are identified using process mining techniques, and an optimized process plan is generated. 【0772】 Based on the generated process plan, the server deploys general-purpose intelligent agents to each business process and begins operation using configuration methods. This involves agents using AI models, and real-time communication using WebSocket is used for overall system coordination. 【0773】 Furthermore, feedback tailored to the user's emotions is reflected in the agent through an emotion analysis system that analyzes the user's psychological state in real time. This process is performed using natural language processing models such as Hugging Face Transformers. The system receives user feedback through a management system and uses it as data for evaluation and improvement. 【0774】 As a concrete example, in a video streaming application, if the system analyzes that a user is experiencing stress, the server will recommend enjoyable content. In this case, the generative AI model can be prompted with a prompt such as, "Suggest video genres that match the user's desired emotions," providing instructions for appropriate content recommendations. This system enables personalized responses tailored to each user's individual emotions. 【0775】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0776】 Step 1: 【0777】 The server collects business data from terminals in each business department. This includes transaction information from the sales department and work logs from the manufacturing department. The collected data is used as input by an information processing system and formatted into an appropriate format. The formatted business data is then output. 【0778】 Step 2: 【0779】 The server analyzes formatted business data using process mining techniques. It analyzes the data using Python and Pandas to identify business processes. Using formatted business data as input, it generates the identified business processes as output. Specifically, it performs data pattern recognition and statistical analysis. 【0780】 Step 3: 【0781】 The server generates an optimized process plan based on the identified business processes. It utilizes processing tools and AI models to perform calculations to optimize the processes. The input data is the identified business processes, and the output is the optimized process plan. The operation includes simulating and evaluating multiple process options. 【0782】 Step 4: 【0783】 The server deploys and operates general-purpose intelligent agents to each business process based on an optimized process plan. Using a configuration method, it communicates in real time via WebSocket and directs the agents to operate according to instructions. The input is the optimized process plan, and the output is the results of the agent's operation. Specifically, it initiates agents and sends commands. 【0784】 Step 5: 【0785】 The server analyzes the user's psychological state using emotion analysis tools. It uses natural language processing models such as Hugging Face Transformers to convert user voice and text data into emotion data. The input data is the user's communication log, and the output is the user's emotional state. Specifically, it performs voice analysis and text emotion analysis. 【0786】 Step 6: 【0787】 The server reflects the analyzed user's emotional state in the operation of the aforementioned agent. Using management tools, it generates responses adapted to the emotion and provides feedback to the agent. The input is the user's emotional state, and the output is the agent's response result. The prompt is "Generate a response that matches the emotion the user desires." The specific actions involve generating or modifying the response. 【0788】 Step 7: 【0789】 The user receives the agent's response and evaluates it. The server processes the evaluation results using management tools and uses them for continuous system improvement. The input data is the user's evaluation, and the output is the improved agent performance. Specific operations include collecting and analyzing feedback. 【0790】 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. 【0791】 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. 【0792】 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. 【0793】 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. 【0794】 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. 【0795】 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. 【0796】 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. 【0797】 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. 【0798】 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." 【0799】 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. 【0800】 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. 【0801】 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. 【0802】 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. 【0803】 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. 【0804】 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. 【0805】 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. 【0806】 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. 【0807】 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. 【0808】 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. 【0809】 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. 【0810】 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. 【0811】 The following is further disclosed regarding the embodiments described above. 【0812】 (Claim 1) 【0813】 Information processing means for collecting business data, 【0814】 Processing means for identifying business processes and generating an optimized process plan by analyzing the aforementioned collected business data, 【0815】 A configuration means for deploying and operating artificial intelligence agents in each business process based on the aforementioned process plan, 【0816】 Control means for monitoring the operation of the artificial intelligence agent and adjusting it based on feedback, 【0817】 A system that includes this. 【0818】 (Claim 2) 【0819】 The system according to claim 1, further comprising means for applying process mining technology using data collected by the aforementioned information processing means. 【0820】 (Claim 3) 【0821】 The system according to claim 1, wherein the control means comprises means for implementing continuous improvements to prevent the obsolescence of the artificial intelligence agent. 【0822】 "Example 1" 【0823】 (Claim 1) 【0824】 Information processing means for collecting business information, 【0825】 Processing means for identifying business processes and generating optimized process plans by analyzing the collected business information, 【0826】 A deployment means for deploying and operating automated agents in each business process based on the aforementioned process plan, 【0827】 Control means for monitoring the operation of the automated agent and adjusting it based on feedback, 【0828】 An analysis means that applies process analysis techniques to the data collected by the aforementioned information processing means, 【0829】 The control means includes an improvement means that implements continuous improvement of the agent, 【0830】 A system that includes this. 【0831】 (Claim 2) 【0832】 The system according to claim 1, wherein the processing means comprises means for optimizing the process plan using a generated AI model. 【0833】 (Claim 3) 【0834】 The system according to claim 1, wherein the control means includes means for automatically adjusting prompt sentences in order to improve the response accuracy of the agent. 【0835】 "Application Example 1" 【0836】 (Claim 1) 【0837】 A data processing method for collecting business information, 【0838】 A calculation means that identifies business procedures by analyzing the collected business information and generates an optimized procedure plan, 【0839】 A deployment means for deploying and operating artificial intelligence agents in each work procedure based on the aforementioned procedure plan, 【0840】 A visualization method to monitor the status of factory operations in real time and identify bottlenecks, 【0841】 Management and control means for monitoring the operation of the artificial intelligence agent and adjusting it based on feedback, 【0842】 A system that includes this. 【0843】 (Claim 2) 【0844】 The system according to claim 1, comprising means for applying process analysis technology using data collected by the information processing means, and including management means for detecting and proposing abnormalities in the manufacturing procedure. 【0845】 (Claim 3) 【0846】 The system according to claim 1, wherein the management and control means includes means for implementing continuous improvements to prevent the obsolescence of the artificial intelligence agent and for improving work efficiency at the manufacturing site. 【0847】 "Example 2 of combining an emotion engine" 【0848】 (Claim 1) 【0849】 Data acquisition methods for collecting business information, 【0850】 Information analysis means for analyzing the acquired business information, identifying business procedures, and generating an optimized procedure plan, 【0851】 Based on the aforementioned procedure plan, the intelligent program is deployed to each work procedure, and a means for deploying and operating it is provided. 【0852】 An integrated means that integrates emotion recognition functionality into an intelligent program, detects the user's emotional state, and reflects it in the response, 【0853】 Control means for monitoring the operation of the intelligent program and adjusting it based on feedback, 【0854】 A system that includes this. 【0855】 (Claim 2) 【0856】 The system according to claim 1, further comprising means for applying business procedure analysis technology using information collected by the data acquisition means. 【0857】 (Claim 3) 【0858】 The system according to claim 1, wherein the control means comprises means for implementing continuous improvements to prevent the intelligent program from becoming obsolete. 【0859】 "Application example 2 when combining with an emotional engine" 【0860】 (Claim 1) 【0861】 Information processing means for collecting business data, 【0862】 Processing means for identifying business processes and generating an optimized process plan by analyzing the aforementioned collected business data, 【0863】 A configuration means for deploying and operating general-purpose intelligent agents in each business process based on the aforementioned process plan, 【0864】 Management means for monitoring the operation of the general-purpose intelligent agent and adjusting it based on feedback, 【0865】 An emotion analysis method that analyzes the user's psychological state and reflects that information in the response of a general-purpose intelligent agent, 【0866】 A system that includes this. 【0867】 (Claim 2) 【0868】 The system according to claim 1, further comprising means for applying process mining technology using data collected by the aforementioned information processing means. 【0869】 (Claim 3) 【0870】 The system according to claim 1, wherein the management means comprises means for implementing continuous improvements to prevent the general-purpose intelligent agent from becoming obsolete. [Explanation of symbols] 【0871】 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] Information processing means for collecting business data, A processing means that identifies business processes by analyzing the collected business data and generates an optimized process plan, A configuration means for deploying and operating artificial intelligence agents in each business process based on the aforementioned process plan, Control means for monitoring the operation of the artificial intelligence agent and adjusting it based on feedback, A system that includes this. [Claim 2] The system according to claim 1, further comprising means for applying process mining technology using data collected by the aforementioned information processing means. [Claim 3] The system according to claim 1, wherein the control means is provided with means for implementing continuous improvements to prevent the artificial intelligence agent from becoming obsolete.

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