system

Abstract

We provide the system. [Solution] Means for collecting data, A means of monitoring the functions of an AI agent, Means for managing security status, A means of suggesting multiple AI tools to the user, 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 Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 AI agents independently introduced by each department within an enterprise are in disarray, causing problems such as data fragmentation and reduced business efficiency. There are also problems such as function conflicts, deficiencies, security risks, and difficulties in compliance. These problems undermine the consistency of business operations and are factors hindering the optimal utilization of AI. 【Means for Solving the Problems】 【0005】 This invention solves these problems by providing a system for the integrated management of diverse AI agents within an enterprise. Specifically, it constructs a system that includes means for data collection, means for monitoring the functions of AI agents, means for managing security status, and means for suggesting multiple AI tools to users. This system enables data centralization, optimal function selection, improved security, and appropriate tool suggestions, thereby improving the operational efficiency of the enterprise. 【0006】 "Data collection" is the process of obtaining information from AI agents and aggregating it in a consistent format. 【0007】 "Monitoring" refers to observing and evaluating the functions and performance of an AI agent. 【0008】 "Security status" refers to the situation in which the AI ​​agent is monitored for potential risks and vulnerabilities. 【0009】 "User" refers to an individual or group within a company that uses AI agents to perform their duties. 【0010】 An "AI agent" is a software program designed to automatically perform specific business tasks. 【0011】 "Tool recommendation" is the process of providing users with appropriate advice regarding the selection of AI tools to use. 【0012】 "Function selection" is the act of choosing the most suitable function from among the functions offered by multiple AI agents. [Brief explanation of the drawing] 【0013】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2]It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined. 【Embodiments for Carrying Out the Invention】 【0014】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0015】 First, the terms used in the following description will be explained. 【0016】 In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0017】 In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0018】 In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like. 【0019】 In the following embodiments, the labeled 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), and the like. 【0020】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0021】 [First Embodiment] 【0022】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0023】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0024】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0025】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0026】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0027】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0028】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0029】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0030】 As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30. 【0031】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0032】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0033】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0034】 This invention relates to a system that enables the integrated management and optimal operation of multiple AI agents used within an enterprise. This system is implemented through a program that integrates data collection, function monitoring, security and compliance management, and tool suggestion. 【0035】 Data collection and integration 【0036】 The server periodically collects data from AI agents deployed in each department within the company. For example, the sales department requests customer management data, and the human resources department requests employee work status data, which are then aggregated. Terminals recognize these requests, extract data from each AI agent, and send it to the server. This prevents data fragmentation and forms a centralized database. 【0037】 Function monitoring and optimization 【0038】 The server monitors the capabilities provided by each AI agent based on the received data. For example, it evaluates the accuracy and processing speed of agents performing predictive analytics and compares them with other agents that have similar capabilities. The user receives reports from the server and selects which capabilities to continue using as needed. 【0039】 Security and Compliance Management 【0040】 The server continuously monitors the security status of each agent and updates the information if vulnerabilities are detected. For example, it automatically applies external security patches. Regarding compliance, it checks whether the data handled by agents in each department conforms to regulations and notifies the server if violations are found. 【0041】 Tool suggestions and user support 【0042】 When a user starts a new project, the server suggests the most suitable AI tools based on the project's objectives and requirements, and generates guidelines explaining how to use them. This information is then communicated to the user via their device. This allows the user to manage the project accurately and efficiently. 【0043】 In this way, the invention helps individual AI agents function optimally and improve the overall operational efficiency of the company. 【0044】 The following describes the processing flow. 【0045】 Step 1: 【0046】 The server sends data collection requests to all AI agents within the enterprise. These requests include the type and scope of data to be collected. 【0047】 Step 2: 【0048】 Each AI agent on the terminal receives a request from the server and extracts the specified data. It then formats the data and sends it back to the server. 【0049】 Step 3: 【0050】 The server aggregates the received data and stores it in a unified database. This database ensures data consistency across departments and is used as the basis for analysis. 【0051】 Step 4: 【0052】 The server monitors the functionality of each AI agent and evaluates their performance. It detects duplication and deficiencies in functionality and generates reports to select the optimal agent. 【0053】 Step 5: 【0054】 The user reviews reports from the server and decides which AI agent to use in their business process. They provide feedback to the server as needed. 【0055】 Step 6: 【0056】 The server monitors the security status of each agent, immediately notifies them if vulnerabilities are discovered, and applies the necessary security patches. 【0057】 Step 7: 【0058】 The server audits the agent's operation logs to verify that activities are being carried out in accordance with compliance measures. If inappropriate behavior is detected, an alert is issued. 【0059】 Step 8: 【0060】 When a user starts a new project, the server suggests appropriate AI tools based on the nature of the project. 【0061】 Step 9: 【0062】 The server selects the most suitable tools based on project requirements and provides users with a guide explaining how to use those tools and their benefits. 【0063】 Step 10: 【0064】 The terminal displays guideline information from the server to the user, providing support to ensure the smooth progress of the project. 【0065】 (Example 1) 【0066】 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." 【0067】 Effectively managing the functions of multiple knowledge processing agents within an enterprise and creating an environment where each agent functions optimally is no easy task. Furthermore, it is necessary to prevent data fragmentation, manage information efficiently, and simultaneously maintain security and compliance. Additionally, it is required that users be able to select the appropriate knowledge processing technology for multiple projects. 【0068】 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. 【0069】 In this invention, the server includes means for collecting data, means for monitoring the functionality of knowledge processing agents, and means for managing the information security status. This enables centralized data management, maintenance of optimal agent performance, and effective technical proposals for each project. 【0070】 "Data collection" is the process of gathering specific information from each department and consolidating it into a centralized information resource. 【0071】 A "knowledge processing agent" is software or a program designed to automate specific information processing tasks. 【0072】 "Monitoring functionality" refers to the continuous observation activity of regularly evaluating the operational performance of each agent to maintain optimal operating conditions. 【0073】 "Information security status" refers to a state in which data within a system is protected from threats and breaches, and the data can be used with peace of mind. 【0074】 A "centralized storage device" is a database or information management system that integrates and centrally manages data collected from multiple sources. 【0075】 "Generating a report" refers to the act of organizing the results and evaluations obtained from analyzing data into a document and processing it into a format for information provision. 【0076】 "Evaluating operational performance" is the process of measuring, using numerical values ​​and other methods, how well an agent is achieving its set objectives, and then determining its efficiency and accuracy. 【0077】 "Providing operational guidelines" refers to the activity of providing specific operational procedures and recommendations on how to operate the agent based on its usage. 【0078】 This invention provides a system that enables centralized management of knowledge processing agents within a company and facilitates their optimal operation. 【0079】 The server collects data from agents deployed in each department and stores it in a centralized database. During this data collection process, the server efficiently manages the collected information using enterprise-grade data management software (such as MySQL® or PostgreSQL). Furthermore, statistical analysis software and generative AI models are used for data analysis. This allows for the evaluation of each agent's performance and the automatic generation of reports based on the results. 【0080】 The terminal is responsible for notifying the user of information sent from the server. This allows the user to check the agent's operational status and performance evaluation results in real time and make necessary decisions quickly. The terminal communicates with the server via application software running on a common operating system (e.g., a web browser or mobile app). Various notifications are delivered to the user via email or push notifications. 【0081】 When users launch a new project or campaign, they receive guidelines from the server on how to utilize recommended knowledge processing technologies. This allows users to manage their projects more efficiently. The server identifies the necessary functions based on the project's objectives and suggests the most suitable tools. This process utilizes common business tools such as Google® Analytics and Tableau. 【0082】 As a concrete example, if a user wants to perform marketing analysis, the server will suggest a data analysis tool and its usage guidelines. An example of a prompt message would be, "Please suggest a data analysis tool suitable for new product market research and its implementation guidelines." This invention supports the efficient operation of knowledge processing agents across the entire enterprise and enables advanced information utilization. 【0083】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0084】 Step 1: 【0085】 The server collects necessary data from knowledge processing agents located in each department within the company. It receives system logs and processing result data from each agent as input. The server then processes this data to eliminate duplication and format it into a standard format in order to integrate it into a centralized database. The output is a formatted, integrated dataset. 【0086】 Step 2: 【0087】 The server uses an integrated dataset to evaluate the performance of each knowledge processing agent. As input, it processes the formatted dataset through an analysis tool and uses a generated AI model to calculate evaluation metrics (e.g., accuracy, processing speed). As output, it generates a report containing the evaluation results. Based on this information, the server performs specific actions to determine the optimal operating state for each agent. 【0088】 Step 3: 【0089】 The terminal notifies the user of the evaluation report received from the server. It receives the evaluation report generated by the server as input. The terminal converts this into a human-readable format and sends it to the user via email or push notification. The output is the report notified to the user. The terminal automates this notification process and operates specifically to ensure the user receives information in a timely manner. 【0090】 Step 4: 【0091】 Based on the notified reports, users select the most suitable knowledge processing technology for their new project and application. They refer to evaluation reports and additional information as input, create prompt statements, and send requests to the server. As output, they receive tools suitable for the project and implementation guidelines. Users utilize example prompt statements to concretely advance their projects. 【0092】 (Application Example 1) 【0093】 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." 【0094】 When multiple artificial intelligence agents are operated independently within a company, data fragmentation occurs, leading to a decrease in overall efficiency. Furthermore, individually monitoring and managing the operational status of each agent increases the burden on human resources. In addition, there are challenges in real-time monitoring of security vulnerabilities and compliance status. 【0095】 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. 【0096】 In this invention, the server includes means for acquiring data, means for monitoring the functions of the artificial intelligence agent, means for managing security, means for proposing multiple artificial intelligence methods to the user, means for visualizing operational data, and means for providing real-time notifications. This enables integrated management of each agent within the enterprise, improving operational efficiency and strengthening security. 【0097】 "Data acquisition" refers to the process of collecting necessary information from each artificial intelligence agent. 【0098】 An "artificial intelligence agent" is an AI program that is trained and executed to achieve a specific purpose. 【0099】 "Monitoring functionality" means continuously tracking the operating status of an artificial intelligence agent and evaluating its performance and efficiency. 【0100】 "Security management" refers to the process of ensuring that the data and functions processed by artificial intelligence agents comply with security standards. 【0101】 A "user" is a person who operates or utilizes the system. 【0102】 "Artificial intelligence techniques" refer to AI technologies and processes used to perform specific tasks. 【0103】 "Visualizing operational data" means displaying quantitative information in a graphical format to make it easier to understand. 【0104】 "Real-time notification" is a process that immediately transmits information about events or anomalies to users. 【0105】 One embodiment of the present invention is a program for the integrated management and efficient operation of multiple artificial intelligence agents within an enterprise. The server periodically acquires data from each artificial intelligence agent and stores this data in a unified database. Data collection is performed via an API and managed systematically using a MySQL database. Additionally, the server has the functionality to monitor the performance of each agent and evaluate operational efficiency and processing performance. This includes a process for monitoring the operating status of each agent and analyzing the data. 【0106】 Users can visualize operational data provided by the server using Tableau as a third-party tool, and gain performance insights using Power BI. This visualization allows for a clear understanding of agent activity and resource usage. 【0107】 Furthermore, the server also performs security management and has functions to monitor security vulnerabilities and compliance status. If a vulnerability is detected, AWS® Lambda is used to automatically execute a remedial process and notify the administrator in real time via Twilio. 【0108】 For example, if resource usage suddenly increases, the system immediately detects the anomaly and sends an alert to the user stating, "Resource usage has exceeded 80%. Please adjust the operating time of the artificial intelligence agent." In this way, integrated management and optimization of artificial intelligence agents within the enterprise are achieved. 【0109】 Example of a prompt: 【0110】 Design an application that collects operational data from artificial intelligence agents within a data center, analyzes and displays resource usage and security anomalies, and notifies administrators of alerts as needed. 【0111】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0112】 Step 1: 【0113】 The server periodically receives data retrieval requests from each artificial intelligence agent. The input requires the agent's API endpoint and authentication information. The data retrieval outputs operational information and performance metrics for each agent. During this process, the server makes API calls and retrieves data in JSON format. 【0114】 Step 2: 【0115】 The server integrates the acquired data into a MySQL database. Raw data obtained from the API is used as input. The server organizes the data and inserts / updates it into the appropriate tables in the database. This ensures that all agent data is centrally managed and output. 【0116】 Step 3: 【0117】 The server analyzes data integrated into the database and monitors the performance of each agent. The input is the contents of the integrated database. The server applies an analysis algorithm and generates a performance report. The analysis results include performance metrics and reports of abnormal conditions. 【0118】 Step 4: 【0119】 Users receive analytical reports from the server and visualize them using conventional business intelligence tools. The input is the data analysis results received from the server. Users visualize the data and generate operational dashboards using tools like Tableau or Power BI. The output of this step is a visually represented report. 【0120】 Step 5: 【0121】 The server provides real-time notifications when it detects performance or security anomalies. The inputs used are analyzed performance data and pre-configured thresholds. The server automatically responds via AWS Lambda and sends notifications using the Twilio API. The output of this step is a real-time alert indicating a situation requiring action. 【0122】 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. 【0123】 This invention relates to a system that comprehensively manages AI agents used within a company and further optimizes business processes by leveraging user emotion data. This system integrates data collection, AI agent function monitoring, security management, tool recommendations to users, and feedback functions using an emotion engine. 【0124】 Data collection and integration 【0125】 The server collects data from AI agents deployed in various departments within the company and integrates it into a centralized database. The emotion engine also collects emotional data through user interfaces. For example, it monitors the stress and satisfaction levels users experience with work tasks in real time. 【0126】 Function monitoring and utilization of emotional data 【0127】 The server monitors the functionality of each AI agent, detecting any duplication or deficiencies. Simultaneously, it analyzes emotional data from the emotion engine and incorporates the results into the AI ​​agent optimization process. For example, if a user's stress level increases, it generates an alert to distribute the workload to the appropriate agent. 【0128】 Security and Compliance Management 【0129】 The server monitors the security status of each agent and automatically applies necessary security patches. It also checks whether all data, including sentiment data, is compliant and issues alerts if it does not meet the standards. 【0130】 Tool suggestions and feedback for users 【0131】 When a user starts a new project, the emotion engine evaluates the user's state, and the server suggests the most suitable AI tools. These suggestions take the user's emotions into account to provide the most effective user experience. The device displays these suggestions to the user, supporting smooth project progress. 【0132】 In this way, the invention not only enables the integrated management of AI agents but also allows for the utilization of emotional data to improve the user's work experience. 【0133】 The following describes the processing flow. 【0134】 Step 1: 【0135】 The server sends data collection requests from all AI agents within the company. This data includes all information related to the business processes of each department. 【0136】 Step 2: 【0137】 The terminal receives the request, extracts and formats the data held by each AI agent, and sends it to the server. This centralizes the data. 【0138】 Step 3: 【0139】 The server analyzes aggregated data and monitors the functionality of the AI ​​agents. It evaluates performance and determines which agents are working efficiently. 【0140】 Step 4: 【0141】 The device collects user emotion data in real time through an emotion engine. This is based on sensor and feedback information that records user interactions during operation. 【0142】 Step 5: 【0143】 The server analyzes data from the emotion engine to determine the relationship between the user's state and work efficiency. For example, if the stress level is high, it recommends process changes to reduce the workload. 【0144】 Step 6: 【0145】 The server monitors the security status of the AI ​​agents and applies relevant patches if vulnerabilities are found. This process also includes the security of sentiment data. 【0146】 Step 7: 【0147】 When a user starts a new project, they receive tool suggestions from the system. These tool suggestions are selected considering the user's emotional state. 【0148】 Step 8: 【0149】 The terminal guides the user through the proposed AI tools and their usage as the project progresses. This allows the user to carry out their work more smoothly. 【0150】 (Example 2) 【0151】 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." 【0152】 In today's corporate environment, numerous artificial intelligence programs are deployed across various departments, but these are not managed in an integrated manner, resulting in redundant functions and wasted resources. Furthermore, user sentiment is not taken into consideration, preventing sufficient improvements in business process efficiency and user experience. In addition, information security and compliance issues are managed separately, increasing the overall complexity of management. 【0153】 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. 【0154】 In this invention, the server includes means for collecting data, means for monitoring the functions of various artificial intelligence programs, means for managing the information security status, and means for analyzing emotional information and providing feedback. This enables integrated management of artificial intelligence programs, allowing for the execution of optimal business processes utilizing user emotional information and advanced security management. 【0155】 "Means of data collection" refers to devices or software that have the function of acquiring information from various departments within a company and storing it in a centralized database. 【0156】 "Means for monitoring the functions of artificial intelligence programs" refers to devices or software that continuously observe the operating status and performance of various artificial intelligence technologies and notify users if there are any abnormalities or duplications. 【0157】 "Means of managing information security status" include devices or software that verify whether data and systems are exposed to threats, including the application and verification of security policies. 【0158】 "Means of proposing various artificial intelligence tools to users" refers to a device or software that has the function of selecting and presenting available artificial intelligence technologies according to the individual user's situation and needs. 【0159】 "Means for analyzing emotional information and providing feedback" refers to devices or software that collect and analyze data on the user's psychological state and then provide appropriate instructions or support based on the results obtained. 【0160】 The system of the present invention integrates and manages multiple artificial intelligence agents, optimizing business processes by utilizing user emotion information. Its specific form is described below. 【0161】 The server collects business data from artificial intelligence agents deployed in each department. This data collection utilizes data APIs and custom scripts. The acquired data is stored in a database management system, where statistical information is generated and analyzed using SQL queries. Database software such as MySQL or PostgreSQL are often used for this purpose. 【0162】 Users utilize the emotional feedback function provided during work to input emotional information into the system. This emotional data is analyzed by an emotional analysis engine, which employs natural language processing techniques and machine learning algorithms. The results, based on the user's psychological state, are used to optimize work processes. 【0163】 The device displays suggestions for the most suitable artificial intelligence tools for the user. These suggestions take into account the user's emotional state and current work situation. For example, if the user is spending a lot of time creating documents, the device might suggest an automated presentation generation tool. 【0164】 As a concrete example, when a user starts a research project for a new market, a predictive analytics tool is suggested. This tool analyzes collected market data to predict trends. Furthermore, if the system determines that the user's workload is increasing due to sentiment analysis, it will issue an alert to distribute the workload. 【0165】 In business support using generative AI models, an example of a prompt message might be, "Suggest how the user can utilize AI tools in their marketing project." 【0166】 In this way, the present invention makes it possible to comprehensively manage artificial intelligence agents and incorporate user emotion data to improve the work experience. 【0167】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0168】 Step 1: 【0169】 The server collects business data from each department. It retrieves information from data APIs and stores it in a centralized database. The input is business data obtained from each department's data API, and the output is integrated data stored in the database. The server automates data collection using Python scripts and updates the data periodically. 【0170】 Step 2: 【0171】 Users input emotional information through a provided emotional feedback interface. This input data, representing feedback on the user's psychological state, is transmitted to the server in real time. The server analyzes this data using an emotional analysis engine. The output is the analysis result regarding the user's emotional state. Natural language processing and machine learning algorithms are applied to the analysis. 【0172】 Step 3: 【0173】 The server integrates collected business and sentiment data and generates necessary statistics by executing SQL queries using information from the database. The input is business and sentiment data from the integrated database, and the output is analysis results regarding business process performance and user state. The server performs the analysis using data analysis libraries. 【0174】 Step 4: 【0175】 The terminal displays suggestions for the most suitable artificial intelligence tools to the user. The input is analysis results obtained from the server, generating suggestions that take into account the user's work needs and emotional state. The output is the recommended tool presented on the user's screen. The terminal uses a UI component for suggestion display to intuitively present the most suitable AI tool to the user. 【0176】 Step 5: 【0177】 The server manages information security and compliance. It periodically checks the security status of the database and system, and applies patches as needed. Inputs include security logs and system configuration information, while outputs include security reports and action lists for necessary countermeasures. The server uses security software to perform automated scans and vulnerability resolution. 【0178】 (Application Example 2) 【0179】 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". 【0180】 In order to improve the quality of public services in smart cities, it is necessary to effectively utilize citizens' emotional data and optimize services in real time. However, current systems do not adequately analyze emotional data and reflect it in services, which is a challenge in contributing to improving citizen satisfaction. 【0181】 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. 【0182】 In this invention, the server includes means for collecting data, means for monitoring the functions of the AI ​​agent, and means for analyzing emotional data and generating suggestions for optimizing the quality of public services in real time. This enables rapid service improvement suggestions based on citizens' emotional data. 【0183】 "Data collection" is the process of gathering information from each agent, providing the fundamental data necessary for the operation of the entire system. 【0184】 "AI agent function monitoring" refers to the management process of observing and analyzing the activities and performance of an AI agent in order to maintain optimal operation. 【0185】 "Security status management" refers to the monitoring and response necessary to maintain the security of information systems, and is a means of ensuring data protection. 【0186】 "AI tool recommendation" is a process that involves selecting the most suitable artificial intelligence technology based on user needs and providing guidance to promote its use. 【0187】 "Analysis of emotional data" is a method of analyzing emotional information obtained from users and using that information to consider improvements to behavior and services. 【0188】 "Optimizing the quality of public services" refers to adjustments and improvements made to enhance the efficiency and effectiveness of administrative services provided to citizens. 【0189】 This invention provides a system that uses an AI agent leveraging emotional data to improve the quality of public services in smart cities. A server collects data from various departments and uses an emotional engine to analyze citizen feedback in real time. The server aggregates and analyzes information using a data analysis platform (e.g., Apache® Kafka, Elasticsearch®) and performs emotional data analysis through an emotional engine (e.g., IBM Watson®, Microsoft® Azure®). This allows the system to generate suggestions for improving public services based on citizens' emotions and notify city administrators of these suggestions. 【0190】 The device functions as a user interface for smartphones and smart glasses, receiving input from citizens and displaying the analysis results. This allows citizens to visually see how their feedback is reflected. For example, if there are many citizen complaints about the cleanliness of a park, the device collects that information and sends it to a server for improvement suggestions. 【0191】 Users can easily provide feedback through smart devices, resulting in more sophisticated public services. A concrete example of use is the prompt, "Analyze the current state of city parks and citizen satisfaction, and identify areas that need improvement." This prompt is processed by a generative AI model, contributing to the optimization of citizen services. 【0192】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0193】 Step 1: 【0194】 The server collects data from various departments within the smart city. It receives feedback data from AI agents and citizen devices as input. This data is integrated into a central database, and its foundational information is processed to prepare it for real-time processing. 【0195】 Step 2: 【0196】 The server sends the collected data to a data analysis platform. The input is integrated citizen feedback data. Based on this, a data analysis platform (e.g., Apache Kafka) is used to filter particularly relevant information and prepare the results for use in the next step. 【0197】 Step 3: 【0198】 The server uses an emotion engine to analyze filtered citizen feedback. Using the analyzed data as input, the emotion engine (e.g., IBM Watson) determines the citizens' emotional state and processes the data. As output, it generates a detailed analysis report on citizens' stress levels and satisfaction levels. 【0199】 Step 4: 【0200】 The server generates suggestions for improving public services based on the analysis results. It uses a generative AI model to generate specific improvement suggestions that align with the prompt text. It takes the results of sentiment analysis as input and generates information to report improvement suggestions to city administrators as output. 【0201】 Step 5: 【0202】 The terminal serves to notify citizens of suggested information on their smart devices. It receives improvement suggestion messages from the server as input and notifies citizens as output. This notification allows citizens to instantly understand how their feedback is being used. 【0203】 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. 【0204】 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. 【0205】 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. 【0206】 [Second Embodiment] 【0207】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0208】 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. 【0209】 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). 【0210】 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. 【0211】 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. 【0212】 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). 【0213】 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. 【0214】 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. 【0215】 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. 【0216】 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. 【0217】 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. 【0218】 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". 【0219】 This invention relates to a system that enables the integrated management and optimal operation of multiple AI agents used within an enterprise. This system is implemented through a program that integrates data collection, function monitoring, security and compliance management, and tool suggestion. 【0220】 Data collection and integration 【0221】 The server periodically collects data from AI agents deployed in each department within the company. For example, the sales department requests customer management data, and the human resources department requests employee work status data, which are then aggregated. Terminals recognize these requests, extract data from each AI agent, and send it to the server. This prevents data fragmentation and forms a centralized database. 【0222】 Function monitoring and optimization 【0223】 The server monitors the capabilities provided by each AI agent based on the received data. For example, it evaluates the accuracy and processing speed of agents performing predictive analytics and compares them with other agents that have similar capabilities. The user receives reports from the server and selects which capabilities to continue using as needed. 【0224】 Security and Compliance Management 【0225】 The server continuously monitors the security status of each agent and updates the information if vulnerabilities are detected. For example, it automatically applies external security patches. Regarding compliance, it checks whether the data handled by agents in each department conforms to regulations and notifies the server if violations are found. 【0226】 Tool suggestions and user support 【0227】 When a user starts a new project, the server suggests the most suitable AI tools based on the project's objectives and requirements, and generates guidelines explaining how to use them. This information is then communicated to the user via their device. This allows the user to manage the project accurately and efficiently. 【0228】 In this way, the invention helps individual AI agents function optimally and improve the overall operational efficiency of the company. 【0229】 The following describes the processing flow. 【0230】 Step 1: 【0231】 The server sends data collection requests to all AI agents within the enterprise. These requests include the type and scope of data to be collected. 【0232】 Step 2: 【0233】 Each AI agent on the terminal receives a request from the server and extracts the specified data. It then formats the data and sends it back to the server. 【0234】 Step 3: 【0235】 The server aggregates the received data and stores it in a unified database. This database ensures data consistency across departments and is used as the basis for analysis. 【0236】 Step 4: 【0237】 The server monitors the functionality of each AI agent and evaluates their performance. It detects duplication and deficiencies in functionality and generates reports to select the optimal agent. 【0238】 Step 5: 【0239】 The user reviews reports from the server and decides which AI agent to use in their business process. They provide feedback to the server as needed. 【0240】 Step 6: 【0241】 The server monitors the security status of each agent, immediately notifies them if vulnerabilities are discovered, and applies the necessary security patches. 【0242】 Step 7: 【0243】 The server audits the agent's operation logs to verify that activities are being carried out in accordance with compliance measures. If inappropriate behavior is detected, an alert is issued. 【0244】 Step 8: 【0245】 When a user starts a new project, the server suggests appropriate AI tools based on the nature of the project. 【0246】 Step 9: 【0247】 The server selects the most suitable tools based on project requirements and provides users with a guide explaining how to use those tools and their benefits. 【0248】 Step 10: 【0249】 The terminal displays guideline information from the server to the user, providing support to ensure the smooth progress of the project. 【0250】 (Example 1) 【0251】 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." 【0252】 Effectively managing the functions of multiple knowledge processing agents within an enterprise and creating an environment where each agent functions optimally is no easy task. Furthermore, it is necessary to prevent data fragmentation, manage information efficiently, and simultaneously maintain security and compliance. Additionally, it is required that users be able to select the appropriate knowledge processing technology for multiple projects. 【0253】 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. 【0254】 In this invention, the server includes means for collecting data, means for monitoring the functionality of knowledge processing agents, and means for managing the information security status. This enables centralized data management, maintenance of optimal agent performance, and effective technical proposals for each project. 【0255】 "Data collection" is the process of gathering specific information from each department and consolidating it into a centralized information resource. 【0256】 A "knowledge processing agent" is software or a program designed to automate specific information processing tasks. 【0257】 "Monitoring functionality" refers to the continuous observation activity of regularly evaluating the operational performance of each agent to maintain optimal operating conditions. 【0258】 "Information security status" refers to a state in which data within a system is protected from threats and breaches, and the data can be used with peace of mind. 【0259】 A "centralized storage device" is a database or information management system that integrates and centrally manages data collected from multiple sources. 【0260】 "Generating a report" refers to the act of organizing the results and evaluations obtained from analyzing data into a document and processing it into a format for information provision. 【0261】 "Evaluating operational performance" is the process of measuring, using numerical values ​​and other methods, how well an agent is achieving its set objectives, and then determining its efficiency and accuracy. 【0262】 "Providing operational guidelines" refers to the activity of providing specific operational procedures and recommendations on how to operate the agent based on its usage. 【0263】 This invention provides a system that enables centralized management of knowledge processing agents within a company and facilitates their optimal operation. 【0264】 The server collects data from agents deployed in each department and stores it in a centralized database. During this data collection process, the server efficiently manages the collected information using enterprise-grade data management software (such as MySQL or PostgreSQL). Furthermore, statistical analysis software and generative AI models are used for data analysis. This allows for the evaluation of each agent's performance and the automatic generation of reports based on the results. 【0265】 The terminal is responsible for notifying the user of information sent from the server. This allows the user to check the agent's operational status and performance evaluation results in real time and make necessary decisions quickly. The terminal communicates with the server via application software running on a common operating system (e.g., a web browser or mobile app). Various notifications are delivered to the user via email or push notifications. 【0266】 When users launch a new project or campaign, they receive guidelines from the server on how to utilize recommended knowledge processing technologies. This allows users to manage their projects more efficiently. The server identifies the necessary functions based on the project's objectives and suggests the most suitable tools. This process utilizes common business tools such as Google Analytics and Tableau. 【0267】 As a concrete example, if a user wants to perform marketing analysis, the server will suggest a data analysis tool and its usage guidelines. An example of a prompt message would be, "Please suggest a data analysis tool suitable for new product market research and its implementation guidelines." This invention supports the efficient operation of knowledge processing agents across the entire enterprise and enables advanced information utilization. 【0268】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0269】 Step 1: 【0270】 The server collects necessary data from knowledge processing agents located in each department within the company. It receives system logs and processing result data from each agent as input. The server then processes this data to eliminate duplication and format it into a standard format in order to integrate it into a centralized database. The output is a formatted, integrated dataset. 【0271】 Step 2: 【0272】 The server uses an integrated dataset to evaluate the performance of each knowledge processing agent. As input, it processes the formatted dataset through an analysis tool and uses a generated AI model to calculate evaluation metrics (e.g., accuracy, processing speed). As output, it generates a report containing the evaluation results. Based on this information, the server performs specific actions to determine the optimal operating state for each agent. 【0273】 Step 3: 【0274】 The terminal notifies the user of the evaluation report received from the server. It receives the evaluation report generated by the server as input. The terminal converts this into a human-readable format and sends it to the user via email or push notification. The output is the report notified to the user. The terminal automates this notification process and operates specifically to ensure the user receives information in a timely manner. 【0275】 Step 4: 【0276】 Based on the notified reports, users select the most suitable knowledge processing technology for their new project and application. They refer to evaluation reports and additional information as input, create prompt statements, and send requests to the server. As output, they receive tools suitable for the project and implementation guidelines. Users utilize example prompt statements to concretely advance their projects. 【0277】 (Application Example 1) 【0278】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0279】 When multiple artificial intelligence agents are operated independently within a company, data fragmentation occurs, leading to a decrease in overall efficiency. Furthermore, individually monitoring and managing the operational status of each agent increases the burden on human resources. In addition, there are challenges in real-time monitoring of security vulnerabilities and compliance status. 【0280】 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. 【0281】 In this invention, the server includes means for acquiring data, means for monitoring the functions of the artificial intelligence agent, means for managing security, means for proposing multiple artificial intelligence methods to the user, means for visualizing operational data, and means for providing real-time notifications. This enables integrated management of each agent within the enterprise, improving operational efficiency and strengthening security. 【0282】 "Data acquisition" refers to the process of collecting necessary information from each artificial intelligence agent. 【0283】 An "artificial intelligence agent" is an AI program that is trained and executed to achieve a specific purpose. 【0284】 "Monitoring functions" means continuously tracking the operating status of artificial intelligence agents and evaluating performance and efficiency. 【0285】 "Security management" refers to the act of verifying that the data and functions processed by artificial intelligence agents comply with security standards. 【0286】 "User" refers to a human who operates or utilizes the system. 【0287】 "Artificial intelligence techniques" are AI technologies and processes used to perform specific tasks. 【0288】 "Visualizing operation data" means presenting quantitative information in a graphical format to make it easier to understand. 【0289】 "Real-time notification" is a process of immediately transmitting information about events and anomalies that occur to users. 【0290】 The embodiments for implementing the present invention are programs for integrally managing multiple artificial intelligence agents within an enterprise and achieving efficient operation. The server periodically acquires data from each artificial intelligence agent and stores the data in a database that integrates this data. In data collection, information is acquired via an API and is neatly managed using a MySQL database. Additionally, the server has a function of monitoring the functions of each agent and evaluating operation efficiency and processing performance. For this purpose, it includes a process of monitoring the operating status of each agent and analyzing the data. 【0291】 Users can visualize the operation data provided by the server using Tableau as a third-party tool and obtain performance insights using Power BI. Through this visualization, the operating status of the agents and the usage status of resources can be clearly grasped. [[ID=X]] 【0292】 Furthermore, the server also performs security management and has functions to monitor security vulnerabilities and compliance status. If a vulnerability is detected, AWS Lambda is used to automatically execute a remedial process and notify the administrator in real time via Twilio. 【0293】 For example, if resource usage suddenly increases, the system immediately detects the anomaly and sends an alert to the user stating, "Resource usage has exceeded 80%. Please adjust the operating time of the artificial intelligence agent." In this way, integrated management and optimization of artificial intelligence agents within the enterprise are achieved. 【0294】 Example of a prompt: 【0295】 Design an application that collects operational data from artificial intelligence agents within a data center, analyzes and displays resource usage and security anomalies, and notifies administrators of alerts as needed. 【0296】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0297】 Step 1: 【0298】 The server periodically receives data retrieval requests from each artificial intelligence agent. The input requires the agent's API endpoint and authentication information. The data retrieval outputs operational information and performance metrics for each agent. During this process, the server makes API calls and retrieves data in JSON format. 【0299】 Step 2: 【0300】 The server integrates the acquired data into a MySQL database. As input, the raw data obtained from the API is used. The server organizes the data and inserts / updates it into the appropriate tables in the database. As a result, the data of all agents is output in a state of unified management. 【0301】 Step 3: 【0302】 The server analyzes the data integrated into the database and monitors the performance of each agent. As input, the content of the integrated database is used. The server applies an analysis algorithm to generate a performance report. As an analysis result, a report on performance indicators and abnormal states is output. 【0303】 Step 4: 【0304】 The user receives the analysis report provided by the server and visualizes it using conventional business intelligence tools. As input, the data analysis result received from the server is used. The user visualizes through Tableau or Power BI to generate an operation dashboard. The output of this step is a visually represented report. 【0305】 Step 5: 【0306】 When the server detects performance or security anomalies, it notifies in real time. As input, the analyzed performance data and pre-set thresholds are used. The server executes an automatic response through AWS Lambda and uses the Twilio API to send notifications. The output of this step is a real-time alert for situations that require action. 【0307】 Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion. 【0308】 This invention relates to a system that comprehensively manages AI agents used within a company and further optimizes business processes by leveraging user emotion data. This system integrates data collection, AI agent function monitoring, security management, tool recommendations to users, and feedback functions using an emotion engine. 【0309】 Data collection and integration 【0310】 The server collects data from AI agents deployed in various departments within the company and integrates it into a centralized database. The emotion engine also collects emotional data through user interfaces. For example, it monitors the stress and satisfaction levels users experience with work tasks in real time. 【0311】 Function monitoring and utilization of emotional data 【0312】 The server monitors the functionality of each AI agent, detecting any duplication or deficiencies. Simultaneously, it analyzes emotional data from the emotion engine and incorporates the results into the AI ​​agent optimization process. For example, if a user's stress level increases, it generates an alert to distribute the workload to the appropriate agent. 【0313】 Security and Compliance Management 【0314】 The server monitors the security status of each agent and automatically applies necessary security patches. It also checks whether all data, including sentiment data, is compliant and issues alerts if it does not meet the standards. 【0315】 Tool suggestions and feedback for users 【0316】 When a user starts a new project, the emotion engine evaluates the user's state, and the server suggests the most suitable AI tools. These suggestions take the user's emotions into account to provide the most effective user experience. The device displays these suggestions to the user, supporting smooth project progress. 【0317】 In this way, the invention not only enables the integrated management of AI agents but also allows for the utilization of emotional data to improve the user's work experience. 【0318】 The following describes the processing flow. 【0319】 Step 1: 【0320】 The server sends data collection requests from all AI agents within the company. This data includes all information related to the business processes of each department. 【0321】 Step 2: 【0322】 The terminal receives the request, extracts and formats the data held by each AI agent, and sends it to the server. This centralizes the data. 【0323】 Step 3: 【0324】 The server analyzes aggregated data and monitors the functionality of the AI ​​agents. It evaluates performance and determines which agents are working efficiently. 【0325】 Step 4: 【0326】 The device collects user emotion data in real time through an emotion engine. This is based on sensor and feedback information that records user interactions during operation. 【0327】 Step 5: 【0328】 The server analyzes data from the emotion engine to determine the relationship between the user's state and work efficiency. For example, if the stress level is high, it recommends process changes to reduce the workload. 【0329】 Step 6: 【0330】 The server monitors the security status of the AI ​​agents and applies relevant patches if vulnerabilities are found. This process also includes the security of sentiment data. 【0331】 Step 7: 【0332】 When a user starts a new project, they receive tool suggestions from the system. These tool suggestions are selected considering the user's emotional state. 【0333】 Step 8: 【0334】 The terminal guides the user through the proposed AI tools and their usage as the project progresses. This allows the user to carry out their work more smoothly. 【0335】 (Example 2) 【0336】 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". 【0337】 In today's corporate environment, numerous artificial intelligence programs are deployed across various departments, but these are not managed in an integrated manner, resulting in redundant functions and wasted resources. Furthermore, user sentiment is not taken into consideration, preventing sufficient improvements in business process efficiency and user experience. In addition, information security and compliance issues are managed separately, increasing the overall complexity of management. 【0338】 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. 【0339】 In this invention, the server includes means for collecting data, means for monitoring the functions of various artificial intelligence programs, means for managing the information security status, and means for analyzing emotional information and providing feedback. This enables integrated management of artificial intelligence programs, allowing for the execution of optimal business processes utilizing user emotional information and advanced security management. 【0340】 "Means of data collection" refers to devices or software that have the function of acquiring information from various departments within a company and storing it in a centralized database. 【0341】 "Means for monitoring the functions of artificial intelligence programs" refers to devices or software that continuously observe the operating status and performance of various artificial intelligence technologies and notify users if there are any abnormalities or duplications. 【0342】 "Means of managing information security status" include devices or software that verify whether data and systems are exposed to threats, including the application and verification of security policies. 【0343】 "Means of proposing various artificial intelligence tools to users" refers to a device or software that has the function of selecting and presenting available artificial intelligence technologies according to the individual user's situation and needs. 【0344】 "Means for analyzing emotional information and providing feedback" refers to devices or software that collect and analyze data on the user's psychological state and then provide appropriate instructions or support based on the results obtained. 【0345】 The system of the present invention integrates and manages multiple artificial intelligence agents, optimizing business processes by utilizing user emotion information. Its specific form is described below. 【0346】 The server collects business data from artificial intelligence agents deployed in each department. This data collection utilizes data APIs and custom scripts. The acquired data is stored in a database management system, where statistical information is generated and analyzed using SQL queries. Database software such as MySQL or PostgreSQL are often used for this purpose. 【0347】 Users utilize the emotional feedback function provided during work to input emotional information into the system. This emotional data is analyzed by an emotional analysis engine, which employs natural language processing techniques and machine learning algorithms. The results, based on the user's psychological state, are used to optimize work processes. 【0348】 The device displays suggestions for the most suitable artificial intelligence tools for the user. These suggestions take into account the user's emotional state and current work situation. For example, if the user is spending a lot of time creating documents, the device might suggest an automated presentation generation tool. 【0349】 As a concrete example, when a user starts a research project for a new market, a predictive analytics tool is suggested. This tool analyzes collected market data to predict trends. Furthermore, if the system determines that the user's workload is increasing due to sentiment analysis, it will issue an alert to distribute the workload. 【0350】 In business support using generative AI models, an example of a prompt message might be, "Suggest how the user can utilize AI tools in their marketing project." 【0351】 In this way, the present invention makes it possible to comprehensively manage artificial intelligence agents and incorporate user emotion data to improve the work experience. 【0352】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0353】 Step 1: 【0354】 The server collects business data from each department. It retrieves information from data APIs and stores it in a centralized database. The input is business data obtained from each department's data API, and the output is integrated data stored in the database. The server automates data collection using Python scripts and updates the data periodically. 【0355】 Step 2: 【0356】 Users input emotional information through a provided emotional feedback interface. This input data, representing feedback on the user's psychological state, is transmitted to the server in real time. The server analyzes this data using an emotional analysis engine. The output is the analysis result regarding the user's emotional state. Natural language processing and machine learning algorithms are applied to the analysis. 【0357】 Step 3: 【0358】 The server integrates collected business and sentiment data and generates necessary statistics by executing SQL queries using information from the database. The input is business and sentiment data from the integrated database, and the output is analysis results regarding business process performance and user state. The server performs the analysis using data analysis libraries. 【0359】 Step 4: 【0360】 The terminal displays suggestions for the most suitable artificial intelligence tools to the user. The input is analysis results obtained from the server, generating suggestions that take into account the user's work needs and emotional state. The output is the recommended tool presented on the user's screen. The terminal uses a UI component for suggestion display to intuitively present the most suitable AI tool to the user. 【0361】 Step 5: 【0362】 The server manages information security and compliance. It periodically checks the security status of the database and system, and applies patches as needed. Inputs include security logs and system configuration information, while outputs include security reports and action lists for necessary countermeasures. The server uses security software to perform automated scans and vulnerability resolution. 【0363】 (Application Example 2) 【0364】 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." 【0365】 In order to improve the quality of public services in smart cities, it is necessary to effectively utilize citizens' emotional data and optimize services in real time. However, current systems do not adequately analyze emotional data and reflect it in services, which is a challenge in contributing to improving citizen satisfaction. 【0366】 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. 【0367】 In this invention, the server includes means for collecting data, means for monitoring the functions of the AI ​​agent, and means for analyzing emotional data and generating suggestions for optimizing the quality of public services in real time. This enables rapid service improvement suggestions based on citizens' emotional data. 【0368】 "Data collection" is the process of gathering information from each agent, providing the fundamental data necessary for the operation of the entire system. 【0369】 "AI agent function monitoring" refers to the management process of observing and analyzing the activities and performance of an AI agent in order to maintain optimal operation. 【0370】 "Security status management" refers to the monitoring and response necessary to maintain the security of information systems, and is a means of ensuring data protection. 【0371】 "AI tool recommendation" is a process that involves selecting the most suitable artificial intelligence technology based on user needs and providing guidance to promote its use. 【0372】 "Analysis of emotional data" is a method of analyzing emotional information obtained from users and using that information to consider improvements to behavior and services. 【0373】 "Optimizing the quality of public services" refers to adjustments and improvements made to enhance the efficiency and effectiveness of administrative services provided to citizens. 【0374】 This invention provides a system that uses an AI agent leveraging emotional data to improve the quality of public services in smart cities. A server collects data from various departments and uses an emotional engine to analyze citizen feedback in real time. The server aggregates and analyzes information using a data analysis platform (e.g., Apache Kafka, Elasticsearch) and performs emotional data analysis through an emotional engine (e.g., IBM Watson, Microsoft Azure). This allows the system to generate suggestions for improving public services based on citizens' emotions and notify city administrators of these suggestions. 【0375】 The device functions as a user interface for smartphones and smart glasses, receiving input from citizens and displaying the analysis results. This allows citizens to visually see how their feedback is reflected. For example, if there are many citizen complaints about the cleanliness of a park, the device collects that information and sends it to a server for improvement suggestions. 【0376】 Users can easily provide feedback through smart devices, resulting in more sophisticated public services. A concrete example of use is the prompt, "Analyze the current state of city parks and citizen satisfaction, and identify areas that need improvement." This prompt is processed by a generative AI model, contributing to the optimization of citizen services. 【0377】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0378】 Step 1: 【0379】 The server collects data from various departments within the smart city. It receives feedback data from AI agents and citizen devices as input. This data is integrated into a central database, and its foundational information is processed to prepare it for real-time processing. 【0380】 Step 2: 【0381】 The server sends the collected data to a data analysis platform. The input is integrated citizen feedback data. Based on this, a data analysis platform (e.g., Apache Kafka) is used to filter particularly relevant information and prepare the results for use in the next step. 【0382】 Step 3: 【0383】 The server uses an emotion engine to analyze filtered citizen feedback. Using the analyzed data as input, the emotion engine (e.g., IBM Watson) determines the citizens' emotional state and processes the data. As output, it generates a detailed analysis report on citizens' stress levels and satisfaction levels. 【0384】 Step 4: 【0385】 The server generates suggestions for improving public services based on the analysis results. It uses a generation AI model to generate specific improvement suggestions that align with the prompt text. It takes the results of sentiment analysis as input and generates information to report improvement suggestions to city administrators as output. 【0386】 Step 5: 【0387】 The terminal serves to notify citizens of suggested information on their smart devices. It receives improvement suggestion messages from the server as input and notifies citizens as output. This notification allows citizens to instantly understand how their feedback is being used. 【0388】 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. 【0389】 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. 【0390】 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. 【0391】 [Third Embodiment] 【0392】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0393】 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. 【0394】 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). 【0395】 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. 【0396】 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. 【0397】 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). 【0398】 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. 【0399】 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. 【0400】 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. 【0401】 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. 【0402】 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. 【0403】 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". 【0404】 This invention relates to a system that enables the integrated management and optimal operation of multiple AI agents used within an enterprise. This system is implemented through a program that integrates data collection, function monitoring, security and compliance management, and tool suggestion. 【0405】 Data collection and integration 【0406】 The server periodically collects data from AI agents deployed in each department within the company. For example, the sales department requests customer management data, and the human resources department requests employee work status data, which are then aggregated. Terminals recognize these requests, extract data from each AI agent, and send it to the server. This prevents data fragmentation and forms a centralized database. 【0407】 Function monitoring and optimization 【0408】 The server monitors the capabilities provided by each AI agent based on the received data. For example, it evaluates the accuracy and processing speed of agents performing predictive analytics and compares them with other agents that have similar capabilities. The user receives reports from the server and selects which capabilities to continue using as needed. 【0409】 Security and Compliance Management 【0410】 The server continuously monitors the security status of each agent and updates the information if vulnerabilities are detected. For example, it automatically applies external security patches. Regarding compliance, it checks whether the data handled by agents in each department conforms to regulations and notifies the server if violations are found. 【0411】 Tool suggestions and user support 【0412】 When a user starts a new project, the server suggests the most suitable AI tools based on the project's objectives and requirements, and generates guidelines explaining how to use them. This information is then communicated to the user via their device. This allows the user to manage the project accurately and efficiently. 【0413】 In this way, the invention helps individual AI agents function optimally and improve the overall operational efficiency of the company. 【0414】 The following describes the processing flow. 【0415】 Step 1: 【0416】 The server sends data collection requests to all AI agents within the enterprise. These requests include the type and scope of data to be collected. 【0417】 Step 2: 【0418】 Each AI agent on the terminal receives a request from the server and extracts the specified data. It then formats the data and sends it back to the server. 【0419】 Step 3: 【0420】 The server aggregates the received data and stores it in a unified database. This database ensures data consistency across departments and is used as the basis for analysis. 【0421】 Step 4: 【0422】 The server monitors the functionality of each AI agent and evaluates their performance. It detects duplication and deficiencies in functionality and generates reports to select the optimal agent. 【0423】 Step 5: 【0424】 The user reviews reports from the server and decides which AI agent to use in their business process. They provide feedback to the server as needed. 【0425】 Step 6: 【0426】 The server monitors the security status of each agent, immediately notifies them if vulnerabilities are discovered, and applies the necessary security patches. 【0427】 Step 7: 【0428】 The server audits the agent's operation logs to verify that activities are being carried out in accordance with compliance measures. If inappropriate behavior is detected, an alert is issued. 【0429】 Step 8: 【0430】 When a user starts a new project, the server suggests appropriate AI tools based on the nature of the project. 【0431】 Step 9: 【0432】 The server selects the most suitable tools based on project requirements and provides users with a guide explaining how to use those tools and their benefits. 【0433】 Step 10: 【0434】 The terminal displays guideline information from the server to the user, providing support to ensure the smooth progress of the project. 【0435】 (Example 1) 【0436】 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." 【0437】 Effectively managing the functions of multiple knowledge processing agents within an enterprise and creating an environment where each agent functions optimally is no easy task. Furthermore, it is necessary to prevent data fragmentation, manage information efficiently, and simultaneously maintain security and compliance. Additionally, it is required that users be able to select the appropriate knowledge processing technology for multiple projects. 【0438】 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. 【0439】 In this invention, the server includes means for collecting data, means for monitoring the functionality of knowledge processing agents, and means for managing the information security status. This enables centralized data management, maintenance of optimal agent performance, and effective technical proposals for each project. 【0440】 "Data collection" is the process of gathering specific information from each department and consolidating it into a centralized information resource. 【0441】 A "knowledge processing agent" is software or a program designed to automate specific information processing tasks. 【0442】 "Monitoring functionality" refers to the continuous observation activity of regularly evaluating the operational performance of each agent to maintain optimal operating conditions. 【0443】 "Information security status" refers to a state in which data within a system is protected from threats and breaches, and the data can be used with peace of mind. 【0444】 A "centralized storage device" is a database or information management system that integrates and centrally manages data collected from multiple sources. 【0445】 "Generating a report" refers to the act of organizing the results and evaluations obtained from analyzing data into a document and processing it into a format for information provision. 【0446】 "Evaluating operational performance" is the process of measuring, using numerical values ​​and other methods, how well an agent is achieving its set objectives, and then determining its efficiency and accuracy. 【0447】 "Providing operational guidelines" refers to the activity of providing specific operational procedures and recommendations on how to operate the agent based on its usage. 【0448】 This invention provides a system that enables centralized management of knowledge processing agents within a company and facilitates their optimal operation. 【0449】 The server collects data from agents deployed in each department and stores it in a centralized database. During this data collection process, the server efficiently manages the collected information using enterprise-grade data management software (such as MySQL or PostgreSQL). Furthermore, statistical analysis software and generative AI models are used for data analysis. This allows for the evaluation of each agent's performance and the automatic generation of reports based on the results. 【0450】 The terminal is responsible for notifying the user of information sent from the server. This allows the user to check the agent's operational status and performance evaluation results in real time and make necessary decisions quickly. The terminal communicates with the server via application software running on a common operating system (e.g., a web browser or mobile app). Various notifications are delivered to the user via email or push notifications. 【0451】 When users launch a new project or campaign, they receive guidelines from the server on how to utilize recommended knowledge processing technologies. This allows users to manage their projects more efficiently. The server identifies the necessary functions based on the project's objectives and suggests the most suitable tools. This process utilizes common business tools such as Google Analytics and Tableau. 【0452】 As a concrete example, if a user wants to perform marketing analysis, the server will suggest a data analysis tool and its usage guidelines. An example of a prompt message would be, "Please suggest a data analysis tool suitable for new product market research and its implementation guidelines." This invention supports the efficient operation of knowledge processing agents across the entire enterprise and enables advanced information utilization. 【0453】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0454】 Step 1: 【0455】 The server collects necessary data from knowledge processing agents located in each department within the company. It receives system logs and processing result data from each agent as input. The server then processes this data to eliminate duplication and format it into a standard format in order to integrate it into a centralized database. The output is a formatted, integrated dataset. 【0456】 Step 2: 【0457】 The server uses an integrated dataset to evaluate the performance of each knowledge processing agent. As input, it processes the formatted dataset through an analysis tool and uses a generated AI model to calculate evaluation metrics (e.g., accuracy, processing speed). As output, it generates a report containing the evaluation results. Based on this information, the server performs specific actions to determine the optimal operating state for each agent. 【0458】 Step 3: 【0459】 The terminal notifies the user of the evaluation report received from the server. It receives the evaluation report generated by the server as input. The terminal converts this into a human-readable format and sends it to the user via email or push notification. The output is the report notified to the user. The terminal automates this notification process and operates specifically to ensure the user receives information in a timely manner. 【0460】 Step 4: 【0461】 Based on the notified reports, users select the most suitable knowledge processing technology for their new project and application. They refer to evaluation reports and additional information as input, create prompt statements, and send requests to the server. As output, they receive tools suitable for the project and implementation guidelines. Users utilize example prompt statements to concretely advance their projects. 【0462】 (Application Example 1) 【0463】 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." 【0464】 When multiple artificial intelligence agents are operated independently within a company, data fragmentation occurs, leading to a decrease in overall efficiency. Furthermore, individually monitoring and managing the operational status of each agent increases the burden on human resources. In addition, there are challenges in real-time monitoring of security vulnerabilities and compliance status. 【0465】 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. 【0466】 In this invention, the server includes means for acquiring data, means for monitoring the functions of the artificial intelligence agent, means for managing security, means for proposing multiple artificial intelligence methods to the user, means for visualizing operational data, and means for providing real-time notifications. This enables integrated management of each agent within the enterprise, improving operational efficiency and strengthening security. 【0467】 "Data acquisition" refers to the process of collecting necessary information from each artificial intelligence agent. 【0468】 An "artificial intelligence agent" is an AI program that is trained and executed to achieve a specific purpose. 【0469】 "Monitoring functionality" means continuously tracking the operating status of an artificial intelligence agent and evaluating its performance and efficiency. 【0470】 "Security management" refers to the process of ensuring that the data and functions processed by artificial intelligence agents comply with security standards. 【0471】 A "user" is a person who operates or utilizes the system. 【0472】 "Artificial intelligence techniques" refer to AI technologies and processes used to perform specific tasks. 【0473】 "Visualizing operational data" means displaying quantitative information in a graphical format to make it easier to understand. 【0474】 "Real-time notification" is a process that immediately transmits information about events or anomalies to users. 【0475】 One embodiment of the present invention is a program for the integrated management and efficient operation of multiple artificial intelligence agents within an enterprise. The server periodically acquires data from each artificial intelligence agent and stores this data in a unified database. Data collection is performed via an API and managed systematically using a MySQL database. Additionally, the server has the functionality to monitor the performance of each agent and evaluate operational efficiency and processing performance. This includes a process for monitoring the operating status of each agent and analyzing the data. 【0476】 Users can visualize operational data provided by the server using Tableau as a third-party tool, and gain performance insights using Power BI. This visualization allows for a clear understanding of agent activity and resource usage. 【0477】 Furthermore, the server also performs security management and has functions to monitor security vulnerabilities and compliance status. If a vulnerability is detected, AWS Lambda is used to automatically execute a remedial process and notify the administrator in real time via Twilio. 【0478】 For example, if resource usage suddenly increases, the system immediately detects the anomaly and sends an alert to the user stating, "Resource usage has exceeded 80%. Please adjust the operating time of the artificial intelligence agent." In this way, integrated management and optimization of artificial intelligence agents within the enterprise are achieved. 【0479】 Example of a prompt: 【0480】 Design an application that collects operational data from artificial intelligence agents within a data center, analyzes and displays resource usage and security anomalies, and notifies administrators of alerts as needed. 【0481】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0482】 Step 1: 【0483】 The server periodically receives data retrieval requests from each artificial intelligence agent. The input requires the agent's API endpoint and authentication information. The data retrieval outputs operational information and performance metrics for each agent. During this process, the server makes API calls and retrieves data in JSON format. 【0484】 Step 2: 【0485】 The server integrates the acquired data into a MySQL database. Raw data obtained from the API is used as input. The server organizes the data and inserts / updates it into the appropriate tables in the database. This ensures that all agent data is centrally managed and output. 【0486】 Step 3: 【0487】 The server analyzes data integrated into the database and monitors the performance of each agent. The input is the contents of the integrated database. The server applies an analysis algorithm and generates a performance report. The analysis results include performance metrics and reports of abnormal conditions. 【0488】 Step 4: 【0489】 Users receive analytical reports from the server and visualize them using conventional business intelligence tools. The input is the data analysis results received from the server. Users visualize the data and generate operational dashboards using tools like Tableau or Power BI. The output of this step is a visually represented report. 【0490】 Step 5: 【0491】 The server provides real-time notifications when it detects performance or security anomalies. The inputs used are analyzed performance data and pre-configured thresholds. The server automatically responds via AWS Lambda and sends notifications using the Twilio API. The output of this step is a real-time alert indicating a situation requiring action. 【0492】 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. 【0493】 This invention relates to a system that comprehensively manages AI agents used within a company and further optimizes business processes by leveraging user emotion data. This system integrates data collection, AI agent function monitoring, security management, tool recommendations to users, and feedback functions using an emotion engine. 【0494】 Data collection and integration 【0495】 The server collects data from AI agents deployed in various departments within the company and integrates it into a centralized database. The emotion engine also collects emotional data through user interfaces. For example, it monitors the stress and satisfaction levels users experience with work tasks in real time. 【0496】 Function monitoring and utilization of emotional data 【0497】 The server monitors the functionality of each AI agent, detecting any duplication or deficiencies. Simultaneously, it analyzes emotional data from the emotion engine and incorporates the results into the AI ​​agent optimization process. For example, if a user's stress level increases, it generates an alert to distribute the workload to the appropriate agent. 【0498】 Security and Compliance Management 【0499】 The server monitors the security status of each agent and automatically applies necessary security patches. It also checks whether all data, including sentiment data, is compliant and issues alerts if it does not meet the standards. 【0500】 Tool suggestions and feedback for users 【0501】 When a user starts a new project, the emotion engine evaluates the user's state, and the server suggests the most suitable AI tools. These suggestions take the user's emotions into account to provide the most effective user experience. The device displays these suggestions to the user, supporting smooth project progress. 【0502】 In this way, the invention not only enables the integrated management of AI agents but also allows for the utilization of emotional data to improve the user's work experience. 【0503】 The following describes the processing flow. 【0504】 Step 1: 【0505】 The server sends data collection requests from all AI agents within the company. This data includes all information related to the business processes of each department. 【0506】 Step 2: 【0507】 The terminal receives the request, extracts and formats the data held by each AI agent, and sends it to the server. This centralizes the data. 【0508】 Step 3: 【0509】 The server analyzes aggregated data and monitors the functionality of the AI ​​agents. It evaluates performance and determines which agents are working efficiently. 【0510】 Step 4: 【0511】 The device collects user emotion data in real time through an emotion engine. This is based on sensor and feedback information that records user interactions during operation. 【0512】 Step 5: 【0513】 The server analyzes data from the emotion engine to determine the relationship between the user's state and work efficiency. For example, if the stress level is high, it recommends process changes to reduce the workload. 【0514】 Step 6: 【0515】 The server monitors the security status of the AI ​​agents and applies relevant patches if vulnerabilities are found. This process also includes the security of sentiment data. 【0516】 Step 7: 【0517】 When a user starts a new project, they receive tool suggestions from the system. These tool suggestions are selected considering the user's emotional state. 【0518】 Step 8: 【0519】 The terminal guides the user through the proposed AI tools and their usage as the project progresses. This allows the user to carry out their work more smoothly. 【0520】 (Example 2) 【0521】 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." 【0522】 In today's corporate environment, numerous artificial intelligence programs are deployed across various departments, but these are not managed in an integrated manner, resulting in redundant functions and wasted resources. Furthermore, user sentiment is not taken into consideration, preventing sufficient improvements in business process efficiency and user experience. In addition, information security and compliance issues are managed separately, increasing the overall complexity of management. 【0523】 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. 【0524】 In this invention, the server includes means for collecting data, means for monitoring the functions of various artificial intelligence programs, means for managing the information security status, and means for analyzing emotional information and providing feedback. This enables integrated management of artificial intelligence programs, allowing for the execution of optimal business processes utilizing user emotional information and advanced security management. 【0525】 "Means of data collection" refers to devices or software that have the function of acquiring information from various departments within a company and storing it in a centralized database. 【0526】 "Means for monitoring the functions of artificial intelligence programs" refers to devices or software that continuously observe the operating status and performance of various artificial intelligence technologies and notify users if there are any abnormalities or duplications. 【0527】 "Means of managing information security status" include devices or software that verify whether data and systems are exposed to threats, including the application and verification of security policies. 【0528】 "Means of proposing various artificial intelligence tools to users" refers to a device or software that has the function of selecting and presenting available artificial intelligence technologies according to the individual user's situation and needs. 【0529】 "Means for analyzing emotional information and providing feedback" refers to devices or software that collect and analyze data on the user's psychological state and then provide appropriate instructions or support based on the results obtained. 【0530】 The system of the present invention integrates and manages multiple artificial intelligence agents, optimizing business processes by utilizing user emotion information. Its specific form is described below. 【0531】 The server collects business data from artificial intelligence agents deployed in each department. This data collection utilizes data APIs and custom scripts. The acquired data is stored in a database management system, where statistical information is generated and analyzed using SQL queries. Database software such as MySQL or PostgreSQL are often used for this purpose. 【0532】 Users utilize the emotional feedback function provided during work to input emotional information into the system. This emotional data is analyzed by an emotional analysis engine, which employs natural language processing techniques and machine learning algorithms. The results, based on the user's psychological state, are used to optimize work processes. 【0533】 The device displays suggestions for the most suitable artificial intelligence tools for the user. These suggestions take into account the user's emotional state and current work situation. For example, if the user is spending a lot of time creating documents, the device might suggest an automated presentation generation tool. 【0534】 As a concrete example, when a user starts a research project for a new market, a predictive analytics tool is suggested. This tool analyzes collected market data to predict trends. Furthermore, if the system determines that the user's workload is increasing due to sentiment analysis, it will issue an alert to distribute the workload. 【0535】 In business support using generative AI models, an example of a prompt message might be, "Suggest how the user can utilize AI tools in their marketing project." 【0536】 In this way, the present invention makes it possible to comprehensively manage artificial intelligence agents and incorporate user emotion data to improve the work experience. 【0537】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0538】 Step 1: 【0539】 The server collects business data from each department. It retrieves information from data APIs and stores it in a centralized database. The input is business data obtained from each department's data API, and the output is integrated data stored in the database. The server automates data collection using Python scripts and updates the data periodically. 【0540】 Step 2: 【0541】 Users input emotional information through a provided emotional feedback interface. This input data, representing feedback on the user's psychological state, is transmitted to the server in real time. The server analyzes this data using an emotional analysis engine. The output is the analysis result regarding the user's emotional state. Natural language processing and machine learning algorithms are applied to the analysis. 【0542】 Step 3: 【0543】 The server integrates collected business and sentiment data and generates necessary statistics by executing SQL queries using information from the database. The input is business and sentiment data from the integrated database, and the output is analysis results regarding business process performance and user state. The server performs the analysis using data analysis libraries. 【0544】 Step 4: 【0545】 The terminal displays suggestions for the most suitable artificial intelligence tools to the user. The input is analysis results obtained from the server, generating suggestions that take into account the user's work needs and emotional state. The output is the recommended tool presented on the user's screen. The terminal uses a UI component for suggestion display to intuitively present the most suitable AI tool to the user. 【0546】 Step 5: 【0547】 The server manages information security and compliance. It periodically checks the security status of the database and system, and applies patches as needed. Inputs include security logs and system configuration information, while outputs include security reports and action lists for necessary countermeasures. The server uses security software to perform automated scans and vulnerability resolution. 【0548】 (Application Example 2) 【0549】 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." 【0550】 In order to improve the quality of public services in smart cities, it is necessary to effectively utilize citizens' emotional data and optimize services in real time. However, current systems do not adequately analyze emotional data and reflect it in services, which is a challenge in contributing to improving citizen satisfaction. 【0551】 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. 【0552】 In this invention, the server includes means for collecting data, means for monitoring the functions of the AI ​​agent, and means for analyzing emotional data and generating suggestions for optimizing the quality of public services in real time. This enables rapid service improvement suggestions based on citizens' emotional data. 【0553】 "Data collection" is the process of gathering information from each agent, providing the fundamental data necessary for the operation of the entire system. 【0554】 "AI agent function monitoring" refers to the management process of observing and analyzing the activities and performance of an AI agent in order to maintain optimal operation. 【0555】 "Security status management" refers to the monitoring and response necessary to maintain the security of information systems, and is a means of ensuring data protection. 【0556】 "AI tool recommendation" is a process that involves selecting the most suitable artificial intelligence technology based on user needs and providing guidance to promote its use. 【0557】 "Analysis of emotional data" is a method of analyzing emotional information obtained from users and using that information to consider improvements to behavior and services. 【0558】 "Optimizing the quality of public services" refers to adjustments and improvements made to enhance the efficiency and effectiveness of administrative services provided to citizens. 【0559】 This invention provides a system that uses an AI agent leveraging emotional data to improve the quality of public services in smart cities. A server collects data from various departments and uses an emotional engine to analyze citizen feedback in real time. The server aggregates and analyzes information using a data analysis platform (e.g., Apache Kafka, Elasticsearch) and performs emotional data analysis through an emotional engine (e.g., IBM Watson, Microsoft Azure). This allows the system to generate suggestions for improving public services based on citizens' emotions and notify city administrators of these suggestions. 【0560】 The device functions as a user interface for smartphones and smart glasses, receiving input from citizens and displaying the analysis results. This allows citizens to visually see how their feedback is reflected. For example, if there are many citizen complaints about the cleanliness of a park, the device collects that information and sends it to a server for improvement suggestions. 【0561】 Users can easily provide feedback through smart devices, resulting in more sophisticated public services. A concrete example of use is the prompt, "Analyze the current state of city parks and citizen satisfaction, and identify areas that need improvement." This prompt is processed by a generative AI model, contributing to the optimization of citizen services. 【0562】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0563】 Step 1: 【0564】 The server collects data from various departments within the smart city. It receives feedback data from AI agents and citizen devices as input. This data is integrated into a central database, and its foundational information is processed to prepare it for real-time processing. 【0565】 Step 2: 【0566】 The server sends the collected data to a data analysis platform. The input is integrated citizen feedback data. Based on this, a data analysis platform (e.g., Apache Kafka) is used to filter particularly relevant information and prepare the results for use in the next step. 【0567】 Step 3: 【0568】 The server uses an emotion engine to analyze filtered citizen feedback. Using the analyzed data as input, the emotion engine (e.g., IBM Watson) determines the citizens' emotional state and processes the data. As output, it generates a detailed analysis report on citizens' stress levels and satisfaction levels. 【0569】 Step 4: 【0570】 The server generates suggestions for improving public services based on the analysis results. It uses a generation AI model to generate specific improvement suggestions that align with the prompt text. It takes the results of sentiment analysis as input and generates information to report improvement suggestions to city administrators as output. 【0571】 Step 5: 【0572】 The terminal serves to notify citizens of suggested information on their smart devices. It receives improvement suggestion messages from the server as input and notifies citizens as output. This notification allows citizens to instantly understand how their feedback is being used. 【0573】 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. 【0574】 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. 【0575】 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. 【0576】 [Fourth Embodiment] 【0577】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0578】 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. 【0579】 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). 【0580】 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. 【0581】 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. 【0582】 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). 【0583】 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. 【0584】 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. 【0585】 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. 【0586】 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. 【0587】 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. 【0588】 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. 【0589】 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". 【0590】 This invention relates to a system that enables the integrated management and optimal operation of multiple AI agents used within an enterprise. This system is implemented through a program that integrates data collection, function monitoring, security and compliance management, and tool suggestion. 【0591】 Data collection and integration 【0592】 The server periodically collects data from AI agents deployed in each department within the company. For example, the sales department requests customer management data, and the human resources department requests employee work status data, which are then aggregated. Terminals recognize these requests, extract data from each AI agent, and send it to the server. This prevents data fragmentation and forms a centralized database. 【0593】 Function monitoring and optimization 【0594】 The server monitors the capabilities provided by each AI agent based on the received data. For example, it evaluates the accuracy and processing speed of agents performing predictive analytics and compares them with other agents that have similar capabilities. The user receives reports from the server and selects which capabilities to continue using as needed. 【0595】 Security and Compliance Management 【0596】 The server continuously monitors the security status of each agent and updates the information if vulnerabilities are detected. For example, it automatically applies external security patches. Regarding compliance, it checks whether the data handled by agents in each department conforms to regulations and notifies the server if violations are found. 【0597】 Tool suggestions and user support 【0598】 When a user starts a new project, the server suggests the most suitable AI tools based on the project's objectives and requirements, and generates guidelines explaining how to use them. This information is then communicated to the user via their device. This allows the user to manage the project accurately and efficiently. 【0599】 In this way, the invention helps individual AI agents function optimally and improve the overall operational efficiency of the company. 【0600】 The following describes the processing flow. 【0601】 Step 1: 【0602】 The server sends data collection requests to all AI agents within the enterprise. These requests include the type and scope of data to be collected. 【0603】 Step 2: 【0604】 Each AI agent on the terminal receives a request from the server and extracts the specified data. It then formats the data and sends it back to the server. 【0605】 Step 3: 【0606】 The server aggregates the received data and stores it in a unified database. This database ensures data consistency across departments and is used as the basis for analysis. 【0607】 Step 4: 【0608】 The server monitors the functionality of each AI agent and evaluates their performance. It detects duplication and deficiencies in functionality and generates reports to select the optimal agent. 【0609】 Step 5: 【0610】 The user reviews reports from the server and decides which AI agent to use in their business process. They provide feedback to the server as needed. 【0611】 Step 6: 【0612】 The server monitors the security status of each agent, immediately notifies them if vulnerabilities are discovered, and applies the necessary security patches. 【0613】 Step 7: 【0614】 The server audits the agent's operation logs to verify that activities are being carried out in accordance with compliance measures. If inappropriate behavior is detected, an alert is issued. 【0615】 Step 8: 【0616】 When a user starts a new project, the server suggests appropriate AI tools based on the nature of the project. 【0617】 Step 9: 【0618】 The server selects the most suitable tools based on project requirements and provides users with a guide explaining how to use those tools and their benefits. 【0619】 Step 10: 【0620】 The terminal displays guideline information from the server to the user, providing support to ensure the smooth progress of the project. 【0621】 (Example 1) 【0622】 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". 【0623】 Effectively managing the functions of multiple knowledge processing agents within an enterprise and creating an environment where each agent functions optimally is no easy task. Furthermore, it is necessary to prevent data fragmentation, manage information efficiently, and simultaneously maintain security and compliance. Additionally, it is required that users be able to select the appropriate knowledge processing technology for multiple projects. 【0624】 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. 【0625】 In this invention, the server includes means for collecting data, means for monitoring the functionality of knowledge processing agents, and means for managing the information security status. This enables centralized data management, maintenance of optimal agent performance, and effective technical proposals for each project. 【0626】 "Data collection" is the process of gathering specific information from each department and consolidating it into a centralized information resource. 【0627】 A "knowledge processing agent" is software or a program designed to automate specific information processing tasks. 【0628】 "Monitoring functionality" refers to the continuous observation activity of regularly evaluating the operational performance of each agent to maintain optimal operating conditions. 【0629】 "Information security status" refers to a state in which data within a system is protected from threats and breaches, and the data can be used with peace of mind. 【0630】 A "centralized storage device" is a database or information management system that integrates and centrally manages data collected from multiple sources. 【0631】 "Generating a report" refers to the act of organizing the results and evaluations obtained from analyzing data into a document and processing it into a format for information provision. 【0632】 "Evaluating operational performance" is the process of measuring, using numerical values ​​and other methods, how well an agent is achieving its set objectives, and then determining its efficiency and accuracy. 【0633】 "Providing operational guidelines" refers to the activity of providing specific operational procedures and recommendations on how to operate the agent based on its usage. 【0634】 This invention provides a system that enables centralized management of knowledge processing agents within a company and facilitates their optimal operation. 【0635】 The server collects data from agents deployed in each department and stores it in a centralized database. During this data collection process, the server efficiently manages the collected information using enterprise-grade data management software (such as MySQL or PostgreSQL). Furthermore, statistical analysis software and generative AI models are used for data analysis. This allows for the evaluation of each agent's performance and the automatic generation of reports based on the results. 【0636】 The terminal is responsible for notifying the user of information sent from the server. This allows the user to check the agent's operational status and performance evaluation results in real time and make necessary decisions quickly. The terminal communicates with the server via application software running on a common operating system (e.g., a web browser or mobile app). Various notifications are delivered to the user via email or push notifications. 【0637】 When users launch a new project or campaign, they receive guidelines from the server on how to utilize recommended knowledge processing technologies. This allows users to manage their projects more efficiently. The server identifies the necessary functions based on the project's objectives and suggests the most suitable tools. This process utilizes common business tools such as Google Analytics and Tableau. 【0638】 As a concrete example, if a user wants to perform marketing analysis, the server will suggest a data analysis tool and its usage guidelines. An example of a prompt message would be, "Please suggest a data analysis tool suitable for new product market research and its implementation guidelines." This invention supports the efficient operation of knowledge processing agents across the entire enterprise and enables advanced information utilization. 【0639】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0640】 Step 1: 【0641】 The server collects necessary data from knowledge processing agents located in each department within the company. It receives system logs and processing result data from each agent as input. The server then processes this data to eliminate duplication and format it into a standard format in order to integrate it into a centralized database. The output is a formatted, integrated dataset. 【0642】 Step 2: 【0643】 The server uses an integrated dataset to evaluate the performance of each knowledge processing agent. As input, it processes the formatted dataset through an analysis tool and uses a generated AI model to calculate evaluation metrics (e.g., accuracy, processing speed). As output, it generates a report containing the evaluation results. Based on this information, the server performs specific actions to determine the optimal operating state for each agent. 【0644】 Step 3: 【0645】 The terminal notifies the user of the evaluation report received from the server. It receives the evaluation report generated by the server as input. The terminal converts this into a human-readable format and sends it to the user via email or push notification. The output is the report notified to the user. The terminal automates this notification process and operates specifically to ensure the user receives information in a timely manner. 【0646】 Step 4: 【0647】 Based on the notified reports, users select the most suitable knowledge processing technology for their new project and application. They refer to evaluation reports and additional information as input, create prompt statements, and send requests to the server. As output, they receive tools suitable for the project and implementation guidelines. Users utilize example prompt statements to concretely advance their projects. 【0648】 (Application Example 1) 【0649】 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". 【0650】 When multiple artificial intelligence agents are operated independently within a company, data fragmentation occurs, leading to a decrease in overall efficiency. Furthermore, individually monitoring and managing the operational status of each agent increases the burden on human resources. In addition, there are challenges in real-time monitoring of security vulnerabilities and compliance status. 【0651】 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. 【0652】 In this invention, the server includes means for acquiring data, means for monitoring the functions of the artificial intelligence agent, means for managing security, means for proposing multiple artificial intelligence methods to the user, means for visualizing operational data, and means for providing real-time notifications. This enables integrated management of each agent within the enterprise, improving operational efficiency and strengthening security. 【0653】 "Data acquisition" refers to the process of collecting necessary information from each artificial intelligence agent. 【0654】 An "artificial intelligence agent" is an AI program that is trained and executed to achieve a specific purpose. 【0655】 "Monitoring functionality" means continuously tracking the operating status of an artificial intelligence agent and evaluating its performance and efficiency. 【0656】 "Security management" refers to the process of ensuring that the data and functions processed by artificial intelligence agents comply with security standards. 【0657】 A "user" is a person who operates or utilizes the system. 【0658】 "Artificial intelligence techniques" refer to AI technologies and processes used to perform specific tasks. 【0659】 "Visualizing operational data" means displaying quantitative information in a graphical format to make it easier to understand. 【0660】 "Real-time notification" is a process that immediately transmits information about events or anomalies to users. 【0661】 One embodiment of the present invention is a program for the integrated management and efficient operation of multiple artificial intelligence agents within an enterprise. The server periodically acquires data from each artificial intelligence agent and stores this data in a unified database. Data collection is performed via an API and managed systematically using a MySQL database. Additionally, the server has the functionality to monitor the performance of each agent and evaluate operational efficiency and processing performance. This includes a process for monitoring the operating status of each agent and analyzing the data. 【0662】 Users can visualize operational data provided by the server using Tableau as a third-party tool, and gain performance insights using Power BI. This visualization allows for a clear understanding of agent activity and resource usage. 【0663】 Furthermore, the server also performs security management and has functions to monitor security vulnerabilities and compliance status. If a vulnerability is detected, AWS Lambda is used to automatically execute a remedial process and notify the administrator in real time via Twilio. 【0664】 For example, if resource usage suddenly increases, the system immediately detects the anomaly and sends an alert to the user stating, "Resource usage has exceeded 80%. Please adjust the operating time of the artificial intelligence agent." In this way, integrated management and optimization of artificial intelligence agents within the enterprise are achieved. 【0665】 Example of a prompt: 【0666】 Design an application that collects operational data from artificial intelligence agents within a data center, analyzes and displays resource usage and security anomalies, and notifies administrators of alerts as needed. 【0667】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0668】 Step 1: 【0669】 The server periodically receives data retrieval requests from each artificial intelligence agent. The input requires the agent's API endpoint and authentication information. The data retrieval outputs operational information and performance metrics for each agent. During this process, the server makes API calls and retrieves data in JSON format. 【0670】 Step 2: 【0671】 The server integrates the acquired data into a MySQL database. Raw data obtained from the API is used as input. The server organizes the data and inserts / updates it into the appropriate tables in the database. This ensures that all agent data is centrally managed and output. 【0672】 Step 3: 【0673】 The server analyzes data integrated into the database and monitors the performance of each agent. The input is the contents of the integrated database. The server applies an analysis algorithm and generates a performance report. The analysis results include performance metrics and reports of abnormal conditions. 【0674】 Step 4: 【0675】 Users receive analytical reports from the server and visualize them using conventional business intelligence tools. The input is the data analysis results received from the server. Users visualize the data and generate operational dashboards using tools like Tableau or Power BI. The output of this step is a visually represented report. 【0676】 Step 5: 【0677】 The server provides real-time notifications when it detects performance or security anomalies. The inputs used are analyzed performance data and pre-configured thresholds. The server automatically responds via AWS Lambda and sends notifications using the Twilio API. The output of this step is a real-time alert indicating a situation requiring action. 【0678】 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. 【0679】 This invention relates to a system that comprehensively manages AI agents used within a company and further optimizes business processes by leveraging user emotion data. This system integrates data collection, AI agent function monitoring, security management, tool recommendations to users, and feedback functions using an emotion engine. 【0680】 Data collection and integration 【0681】 The server collects data from AI agents deployed in various departments within the company and integrates it into a centralized database. The emotion engine also collects emotional data through user interfaces. For example, it monitors the stress and satisfaction levels users experience with work tasks in real time. 【0682】 Function monitoring and utilization of emotional data 【0683】 The server monitors the functionality of each AI agent, detecting any duplication or deficiencies. Simultaneously, it analyzes emotional data from the emotion engine and incorporates the results into the AI ​​agent optimization process. For example, if a user's stress level increases, it generates an alert to distribute the workload to the appropriate agent. 【0684】 Security and Compliance Management 【0685】 The server monitors the security status of each agent and automatically applies necessary security patches. It also checks whether all data, including sentiment data, is compliant and issues alerts if it does not meet the standards. 【0686】 Tool suggestions and feedback for users 【0687】 When a user starts a new project, the emotion engine evaluates the user's state, and the server suggests the most suitable AI tools. These suggestions take the user's emotions into account to provide the most effective user experience. The device displays these suggestions to the user, supporting smooth project progress. 【0688】 In this way, the invention not only enables the integrated management of AI agents but also allows for the utilization of emotional data to improve the user's work experience. 【0689】 The following describes the processing flow. 【0690】 Step 1: 【0691】 The server sends data collection requests from all AI agents within the company. This data includes all information related to the business processes of each department. 【0692】 Step 2: 【0693】 The terminal receives the request, extracts and formats the data held by each AI agent, and sends it to the server. This centralizes the data. 【0694】 Step 3: 【0695】 The server analyzes aggregated data and monitors the functionality of the AI ​​agents. It evaluates performance and determines which agents are working efficiently. 【0696】 Step 4: 【0697】 The device collects user emotion data in real time through an emotion engine. This is based on sensor and feedback information that records user interactions during operation. 【0698】 Step 5: 【0699】 The server analyzes data from the emotion engine to determine the relationship between the user's state and work efficiency. For example, if the stress level is high, it recommends process changes to reduce the workload. 【0700】 Step 6: 【0701】 The server monitors the security status of the AI ​​agents and applies relevant patches if vulnerabilities are found. This process also includes the security of sentiment data. 【0702】 Step 7: 【0703】 When a user starts a new project, they receive tool suggestions from the system. These tool suggestions are selected considering the user's emotional state. 【0704】 Step 8: 【0705】 The terminal guides the user through the proposed AI tools and their usage as the project progresses. This allows the user to carry out their work more smoothly. 【0706】 (Example 2) 【0707】 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". 【0708】 In today's corporate environment, numerous artificial intelligence programs are deployed across various departments, but these are not managed in an integrated manner, resulting in redundant functions and wasted resources. Furthermore, user sentiment is not taken into consideration, preventing sufficient improvements in business process efficiency and user experience. In addition, information security and compliance issues are managed separately, increasing the overall complexity of management. 【0709】 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. 【0710】 In this invention, the server includes means for collecting data, means for monitoring the functions of various artificial intelligence programs, means for managing the information security status, and means for analyzing emotional information and providing feedback. This enables integrated management of artificial intelligence programs, allowing for the execution of optimal business processes utilizing user emotional information and advanced security management. 【0711】 "Means of data collection" refers to devices or software that have the function of acquiring information from various departments within a company and storing it in a centralized database. 【0712】 "Means for monitoring the functions of artificial intelligence programs" refers to devices or software that continuously observe the operating status and performance of various artificial intelligence technologies and notify users if there are any abnormalities or duplications. 【0713】 "Means of managing information security status" include devices or software that verify whether data and systems are exposed to threats, including the application and verification of security policies. 【0714】 "Means of proposing various artificial intelligence tools to users" refers to a device or software that has the function of selecting and presenting available artificial intelligence technologies according to the individual user's situation and needs. 【0715】 "Means for analyzing emotional information and providing feedback" refers to devices or software that collect and analyze data on the user's psychological state and then provide appropriate instructions or support based on the results obtained. 【0716】 The system of the present invention integrates and manages multiple artificial intelligence agents, optimizing business processes by utilizing user emotion information. Its specific form is described below. 【0717】 The server collects business data from artificial intelligence agents deployed in each department. This data collection utilizes data APIs and custom scripts. The acquired data is stored in a database management system, where statistical information is generated and analyzed using SQL queries. Database software such as MySQL or PostgreSQL are often used for this purpose. 【0718】 Users utilize the emotional feedback function provided during work to input emotional information into the system. This emotional data is analyzed by an emotional analysis engine, which employs natural language processing techniques and machine learning algorithms. The results, based on the user's psychological state, are used to optimize work processes. 【0719】 The device displays suggestions for the most suitable artificial intelligence tools for the user. These suggestions take into account the user's emotional state and current work situation. For example, if the user is spending a lot of time creating documents, the device might suggest an automated presentation generation tool. 【0720】 As a concrete example, when a user starts a research project for a new market, a predictive analytics tool is suggested. This tool analyzes collected market data to predict trends. Furthermore, if the system determines that the user's workload is increasing due to sentiment analysis, it will issue an alert to distribute the workload. 【0721】 In business support using generative AI models, an example of a prompt message might be, "Suggest how the user can utilize AI tools in their marketing project." 【0722】 In this way, the present invention makes it possible to comprehensively manage artificial intelligence agents and incorporate user emotion data to improve the work experience. 【0723】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0724】 Step 1: 【0725】 The server collects business data from each department. It retrieves information from data APIs and stores it in a centralized database. The input is business data obtained from each department's data API, and the output is integrated data stored in the database. The server automates data collection using Python scripts and updates the data periodically. 【0726】 Step 2: 【0727】 Users input emotional information through a provided emotional feedback interface. This input data, representing feedback on the user's psychological state, is transmitted to the server in real time. The server analyzes this data using an emotional analysis engine. The output is the analysis result regarding the user's emotional state. Natural language processing and machine learning algorithms are applied to the analysis. 【0728】 Step 3: 【0729】 The server integrates collected business and sentiment data and generates necessary statistics by executing SQL queries using information from the database. The input is business and sentiment data from the integrated database, and the output is analysis results regarding business process performance and user state. The server performs the analysis using data analysis libraries. 【0730】 Step 4: 【0731】 The terminal displays suggestions for the most suitable artificial intelligence tools to the user. The input is analysis results obtained from the server, generating suggestions that take into account the user's work needs and emotional state. The output is the recommended tool presented on the user's screen. The terminal uses a UI component for suggestion display to intuitively present the most suitable AI tool to the user. 【0732】 Step 5: 【0733】 The server manages information security and compliance. It periodically checks the security status of the database and system, and applies patches as needed. Inputs include security logs and system configuration information, while outputs include security reports and action lists for necessary countermeasures. The server uses security software to perform automated scans and vulnerability resolution. 【0734】 (Application Example 2) 【0735】 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". 【0736】 In order to improve the quality of public services in smart cities, it is necessary to effectively utilize citizens' emotional data and optimize services in real time. However, current systems do not adequately analyze emotional data and reflect it in services, which is a challenge in contributing to improving citizen satisfaction. 【0737】 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. 【0738】 In this invention, the server includes means for collecting data, means for monitoring the functions of the AI ​​agent, and means for analyzing emotional data and generating suggestions for optimizing the quality of public services in real time. This enables rapid service improvement suggestions based on citizens' emotional data. 【0739】 "Data collection" is the process of gathering information from each agent, providing the fundamental data necessary for the operation of the entire system. 【0740】 "AI agent function monitoring" refers to the management process of observing and analyzing the activities and performance of an AI agent in order to maintain optimal operation. 【0741】 "Security status management" refers to the monitoring and response necessary to maintain the security of information systems, and is a means of ensuring data protection. 【0742】 "AI tool recommendation" is a process that involves selecting the most suitable artificial intelligence technology based on user needs and providing guidance to promote its use. 【0743】 "Analysis of emotional data" is a method of analyzing emotional information obtained from users and using that information to consider improvements to behavior and services. 【0744】 "Optimizing the quality of public services" refers to adjustments and improvements made to enhance the efficiency and effectiveness of administrative services provided to citizens. 【0745】 This invention provides a system that uses an AI agent leveraging emotional data to improve the quality of public services in smart cities. A server collects data from various departments and uses an emotional engine to analyze citizen feedback in real time. The server aggregates and analyzes information using a data analysis platform (e.g., Apache Kafka, Elasticsearch) and performs emotional data analysis through an emotional engine (e.g., IBM Watson, Microsoft Azure). This allows the system to generate suggestions for improving public services based on citizens' emotions and notify city administrators of these suggestions. 【0746】 The device functions as a user interface for smartphones and smart glasses, receiving input from citizens and displaying the analysis results. This allows citizens to visually see how their feedback is reflected. For example, if there are many citizen complaints about the cleanliness of a park, the device collects that information and sends it to a server for improvement suggestions. 【0747】 Users can easily provide feedback through smart devices, resulting in more sophisticated public services. A concrete example of use is the prompt, "Analyze the current state of city parks and citizen satisfaction, and identify areas that need improvement." This prompt is processed by a generative AI model, contributing to the optimization of citizen services. 【0748】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0749】 Step 1: 【0750】 The server collects data from various departments within the smart city. It receives feedback data from AI agents and citizen devices as input. This data is integrated into a central database, and its foundational information is processed to prepare it for real-time processing. 【0751】 Step 2: 【0752】 The server sends the collected data to a data analysis platform. The input is integrated citizen feedback data. Based on this, a data analysis platform (e.g., Apache Kafka) is used to filter particularly relevant information and prepare the results for use in the next step. 【0753】 Step 3: 【0754】 The server uses an emotion engine to analyze filtered citizen feedback. Using the analyzed data as input, the emotion engine (e.g., IBM Watson) determines the citizens' emotional state and processes the data. As output, it generates a detailed analysis report on citizens' stress levels and satisfaction levels. 【0755】 Step 4: 【0756】 The server generates suggestions for improving public services based on the analysis results. It uses a generation AI model to generate specific improvement suggestions that align with the prompt text. It takes the results of sentiment analysis as input and generates information to report improvement suggestions to city administrators as output. 【0757】 Step 5: 【0758】 The terminal serves to notify citizens of suggested information on their smart devices. It receives improvement suggestion messages from the server as input and notifies citizens as output. This notification allows citizens to instantly understand how their feedback is being used. 【0759】 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. 【0760】 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. 【0761】 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. 【0762】 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. 【0763】 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. 【0764】 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. 【0765】 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. 【0766】 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. 【0767】 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." 【0768】 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. 【0769】 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. 【0770】 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. 【0771】 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. 【0772】 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. 【0773】 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. 【0774】 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. 【0775】 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. 【0776】 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. 【0777】 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. 【0778】 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. 【0779】 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. 【0780】 The following is further disclosed regarding the embodiments described above. 【0781】 (Claim 1) 【0782】 Means for collecting data, 【0783】 A means of monitoring the functions of an AI agent, 【0784】 Means for managing security status, 【0785】 A means of suggesting multiple AI tools to the user, 【0786】 A system that includes this. 【0787】 (Claim 2) 【0788】 The system according to claim 1, comprising means for integrating data from each AI agent. 【0789】 (Claim 3) 【0790】 The system according to claim 1, comprising means for detecting overlapping or missing functions and selecting the optimal AI agent. 【0791】 "Example 1" 【0792】 (Claim 1) 【0793】 Means of collecting data, 【0794】 Means for monitoring the functionality of knowledge processing agents, 【0795】 Means for managing the information security status, 【0796】 A means of proposing multiple knowledge processing techniques to users, 【0797】 A means of integrating data into a centralized storage device, 【0798】 A means for evaluating the operational performance of each knowledge processing agent and generating a report, 【0799】 A means of selecting appropriate knowledge processing technology according to different projects, 【0800】 A system that includes this. 【0801】 (Claim 2) 【0802】 The system according to claim 1, which performs processing to prevent data fragmentation and enable efficient information management. 【0803】 (Claim 3) 【0804】 The system according to claim 1, which, based on the generated report, selects the most suitable knowledge processing agent and provides operational guidelines. 【0805】 "Application Example 1" 【0806】 (Claim 1) 【0807】 Means of acquiring data, 【0808】 A means of monitoring the functions of an artificial intelligence agent, 【0809】 Means of managing safety, 【0810】 A means of proposing multiple artificial intelligence methods to users, 【0811】 Means for visualizing operational data, 【0812】 Means of providing real-time notifications, 【0813】 A system that includes this. 【0814】 (Claim 2) 【0815】 The system according to claim 1, comprising means for aggregating information from each artificial intelligence agent. 【0816】 (Claim 3) 【0817】 The system according to claim 1, comprising means for detecting overlapping or missing functions, selecting the optimal artificial intelligence agent, and improving operational efficiency. 【0818】 "Example 2 of combining an emotion engine" 【0819】 (Claim 1) 【0820】 Means of collecting data, 【0821】 Means for monitoring the functions of an artificial intelligence program, 【0822】 Means for managing the information security status, 【0823】 A means of proposing various artificial intelligence tools to users, 【0824】 A means of analyzing emotional information and providing feedback, 【0825】 A system that includes this. 【0826】 (Claim 2) 【0827】 The system according to claim 1, comprising means for integrating information from each artificial intelligence program. 【0828】 (Claim 3) 【0829】 The system according to claim 1, comprising means for detecting duplication or deficiency of functions and selecting the optimal artificial intelligence program, and means for optimizing work by reflecting user sentiment information. 【0830】 "Application example 2 when combining with an emotional engine" 【0831】 (Claim 1) 【0832】 Means for collecting data, 【0833】 A means of monitoring the functions of an AI agent, 【0834】 Means for managing security status, 【0835】 A means of suggesting multiple AI tools to the user, 【0836】 A means of analyzing emotional data and generating suggestions for optimizing the quality of public services in real time, 【0837】 A system that includes this. 【0838】 (Claim 2) 【0839】 The system according to claim 1, comprising means for integrating data from each AI agent. 【0840】 (Claim 3) 【0841】 The system according to claim 1, comprising means for detecting overlapping or missing functions and selecting the optimal AI agent. [Explanation of Symbols] 【0842】 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] Means for collecting data, A means of monitoring the functions of an AI agent, Means for managing security status, A means of suggesting multiple AI tools to the user, A system that includes this. [Claim 2] The system according to claim 1, comprising means for integrating data from each AI agent. [Claim 3] The system according to claim 1, comprising means for detecting duplication or deficiency of functions and selecting the optimal AI agent.

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