Online office staff management system and method based on real-time monitoring

Abstract

The invention discloses an online office staff management method based on real-time monitoring. The method comprises the following specific use steps: S1, generating an attendance report; s2, the working state of online office staff is collected in real time, and data are sent regularly; s3, receiving the data, storing the data to a MySQL database and a MongoDB database, and meanwhile, caching the data by using Redis; s4, updating the online state and the last heartbeat packet time of the online office staff; and S5, analyzing the data, generating a visual chart and a visual curve, and displaying the chart and the curve. Through the system, a manager can master the work progress, the work saturation and the busy degree of online office staff in real time, so that task allocation and human resource scheduling are more reasonably carried out, the overall office efficiency is improved, the online office management efficiency is remarkably improved, and the workload of workers is reduced. Accurate workload analysis and personnel scheduling basis are provided for managers, real-time states and attendance conditions of online office personnel are ensured to be grasped in time, and efficient operation of a working process is promoted.

Description

Technical Field

[0001] The present invention relates to the field of online office personnel management methods, and particularly to an online office personnel management system and method based on real-time monitoring. Background Art

[0002] With the rapid development of information technology, the online office mode has gradually become an important part of modern enterprise management. The demand for remote work has increased significantly, prompting enterprises to strengthen the management and monitoring of online office personnel to ensure work efficiency and smooth team collaboration. Therefore, how to effectively manage the attendance, work status, and workload of online office personnel has become a major challenge for enterprises.

[0003] The existing online office personnel management systems usually have the following problems:

[0004] Insufficiently detailed attendance monitoring: Many systems only rely on regular attendance records and lack the monitoring of the real-time attendance of online office personnel, resulting in the inability to promptly grasp the work status of employees.

[0005] Insufficient data analysis capabilities: Existing systems often cannot conduct in-depth analysis of the work data of online office personnel and lack visual analysis tools, making it difficult for managers to intuitively understand the work saturation and busyness of employees.

[0006] Lack of a real-time feedback mechanism: Most systems fail to promptly feedback the collected data to managers, resulting in managers being unable to make quick decisions and affecting the efficiency of work arrangements and task assignments.

[0007] Unreasonable technical architecture: Some systems do not adopt an efficient architecture for data storage and processing, resulting in slow data access speeds and being unable to meet the performance requirements in high-concurrency scenarios.

[0008] Poor user experience: In terms of user interface design, many systems fail to provide a friendly operation experience, affecting the work enthusiasm and efficiency of online office personnel.

[0009] In response to the above problems, an online office personnel management method and system based on real-time monitoring are proposed, aiming to achieve comprehensive management of online office personnel through various means such as setting work periods, real-time collection of work status, data storage and analysis, and visual display. Summary of the Invention

[0010] The purpose of the present invention is to provide an online office personnel management system and method based on real-time monitoring to solve the problems in the above background art, namely, the inability to real-time monitor the status of online office personnel and the lack of work saturation analysis in existing office systems.

[0011] To achieve the above object, the present invention provides the following technical solutions: An online office staff management method based on real-time monitoring, including the following specific usage steps:

[0012] S1: According to the company's needs, set the working hours of online office staff, monitor the actual attendance of online office staff, and generate an attendance report;

[0013] S2: Real-time collect the working status of online office staff and send data regularly;

[0014] S3: Receive data, store the data in MySQL and MongoDB databases, and use Redis for caching at the same time;

[0015] S4: According to the screenshots and video operations uploaded by the RocketMQ listening front-end client module, update the online status and the last heartbeat packet time of online office staff in a timely manner;

[0016] S5: Analyze the data, generate visual charts and curves, and display them.

[0017] Among them, in step S1, after the generation of the attendance report, based on the attendance status of real-time online office staff, combined with work saturation and busyness data, feedback is given to human resources to optimize the scheduling of office staff.

[0018] Among them, in step S2, the front-end client module maintains a long connection with the back-end client module according to WebSocket, sends the working status of online office staff every once in a while, and the working status includes but is not limited to online status, task progress, keyboard and mouse activities, and running application data.

[0019] Among them, the specific steps of S5 are as follows:

[0020] S51: Dynamically calculate the work saturation and work busyness of online office staff according to the historical work data, real-time task progress, keyboard and mouse activity data, and application information of online office staff;

[0021] S52: Generate visual work saturation charts and work busyness curves;

[0022] S53: Display the charts and curves in the visualization interface.

[0023] Among them, in step S51, the detection method of work busyness is: The system dynamically generates a keyboard work busyness score and a comprehensive keyboard and mouse busyness score according to the monitored keyboard and mouse operation frequencies of online office staff. The algorithm calculates the activity based on the data of the time period, and the scoring result is used to measure the employee's workload.

[0024] Among them, in step S51, the keyboard working busyness scoring formula is:

[0025] When the comprehensive click volume C is lower than the benchmark value A:

[0026]

[0027] The maximum score does not exceed 100 points;

[0028] When the comprehensive click volume C is between the benchmark value A and the upper limit K:

[0029]

[0030] The maximum score does not exceed 100 points;

[0031] When the comprehensive click volume C exceeds the upper limit K:

[0032] B = 99.999;

[0033] Set parameters:

[0034] Among them, C is the comprehensive click volume, A is the preset benchmark average of keyboard clicks, K is the upper limit of keyboard clicks, and K = A × 2, and the result B is the keyboard working busyness score.

[0035] Among them, in step S51, the specific steps for the comprehensive busyness scoring of the keyboard and mouse are:

[0036] S511. First, calculate the comprehensive click volume;

[0037] S512. Calculate the busyness score by calling the scoring function;

[0038] S513. Obtain the final comprehensive busyness score of the keyboard and mouse.

[0039] Among them, in step S511, the calculation formula for the comprehensive click volume is:

[0040] C = K × W K + M × W M ;

[0041] In step S512, the calculation formula for the busyness score is:

[0042] B Z = C × A;

[0043] In step S513, the final calculation formula for the busyness score is:

[0044] B Z = (K × W K + M × W M ) × A;

[0045] Among them, K is the number of keyboard clicks of the user during this time period, M is the number of mouse clicks of the user during this time period, W K is the keyboard click weight, W M is the mouse click weight, A is the preset benchmark average value of keyboard clicks, B Z is the comprehensive busyness score of the keyboard and the mouse.

[0046] An online office staff management system based on real-time monitoring, including:

[0047] A shift scheduling management module, which is used to set the working hours of online office staff according to the company's needs, monitor the actual attendance of online office staff, and generate an attendance report;

[0048] A front-end client module, which is used to collect the working status of online office staff in real time and send data regularly;

[0049] A back-end client module, which is used to receive data, store the data in MySQL and MongoDB databases, and use Redis for caching at the same time;

[0050] A real-time monitoring module, which is used to listen to the screenshots and video operations uploaded by the front-end client module according to RocketMQ, and update the online status and the last heartbeat packet time of online office staff in time;

[0051] A data analysis module, which is used to analyze data, generate visual charts and curves, and display them.

[0052] Among them, the data analysis module visually displays the work saturation chart, work busyness curve and historical work process data through a JavaScript chart library for managers to view and analyze in real time. The back-end client module uses MySQL as the main database to store the status data and task data of online office staff, MongoDB is used to store unstructured data such as videos and graphic records, and Redis is used to cache common data to accelerate data access and improve the system response speed.

[0053] The technical effects and advantages of the present invention:

[0054] (1) Through this system of the present invention, managers can grasp the work progress, work saturation and busyness of online office staff in real time, so as to allocate tasks and schedule human resources more reasonably, improve the overall office efficiency, significantly improve the online office management efficiency, provide managers with accurate workload analysis and personnel scheduling basis, ensure timely grasp of the real-time status and attendance of online office staff, and promote the efficient operation of the work process;

[0055] (2) Through this system, the present invention monitors the real-time attendance status of online office workers, enabling timely acquisition of employees' work conditions and online status, and real-time feedback of relevant data to managers. This real-time nature ensures that managers can quickly identify problems and take corresponding measures, thereby improving work efficiency and team collaboration;

[0056] (3) By dynamically calculating the work saturation and busyness of online office workers and generating visual charts and curves, the present invention helps managers intuitively understand the team's workload and task progress. This data-driven decision-making method contributes to optimizing work arrangements and task allocations, and improving resource utilization;

[0057] (4) Through this system, the present invention establishes a comprehensive work busyness scoring system. Based on data such as the operation frequencies of keyboards and mice, it can scientifically evaluate the work load of online office workers. This scoring mechanism can not only reflect the actual work status of employees, but also targetedly adjust and allocate work tasks to ensure the efficient operation of the team;

[0058] (5) The present invention adopts multiple database technologies such as MySQL, MongoDB, and Redis, combined with an efficient data caching mechanism, significantly improving the speed of data storage and access. This architecture design ensures the stability and response speed of the system in high-concurrency scenarios, meeting the real-time data processing requirements of modern enterprises;

[0059] (6) With the friendly design of the front-end interface of this system of the present invention, online office workers and managers can easily access the required information, enhancing the user operation experience. This optimized user interface design helps improve the work enthusiasm of online office workers, thereby promoting the improvement of work efficiency;

[0060] (7) Through this system, based on real-time attendance data and work saturation analysis, managers can schedule personnel and allocate tasks more flexibly. This flexibility enables managers to adjust work arrangements in a timely manner according to actual situations, improving the overall work efficiency of the team. Brief Description of the Drawings

[0061] Figure 1 It is the system schematic diagram of the present invention. Detailed Embodiments

[0062] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0063] The present invention provides an online office staff management method based on real-time monitoring as Figure 1 shown, including the following specific usage steps:

[0064] S1: According to the company's needs, set the working hours of online office staff, monitor the actual attendance of online office staff, and generate an attendance report;

[0065] S2: Real-time collect the working status of online office staff and send data regularly;

[0066] S3: Receive data, store the data in MySQL and MongoDB databases, and use Redis for caching at the same time;

[0067] S4: According to the screenshots and video operations uploaded by the RocketMQ listening front-end client module, timely update the online status and the last heartbeat packet time of online office staff;

[0068] S5: Analyze the data, generate visual charts and curves, and display them.

[0069] Among them, in step S1, after the generation of the attendance report, based on the attendance status of real-time online office staff, and combined with work saturation and busyness data, feedback on human resources is carried out to optimize the scheduling of office staff.

[0070] Among them, in step S2, the front-end client module maintains a long connection with the back-end client module according to WebSocket, sends the working status of online office staff every 5 minutes, and the working status includes but is not limited to online status, task progress, keyboard and mouse activities, and running application data.

[0071] Among them, the specific steps of S5 are as follows:

[0072] S51: Dynamically calculate the work saturation and work busyness of online office staff according to the historical work data, real-time task progress, keyboard and mouse activity data, and application information of online office staff;

[0073] S52: Generate visual work saturation charts and work busyness curves;

[0074] S53: Display the charts and curves in the visualization interface.

[0075] Among them, in step S51, the detection method of work busyness is: the system dynamically generates a keyboard work busyness score and a comprehensive keyboard and mouse busyness score according to the monitored keyboard and mouse operation frequencies of online office staff. The algorithm calculates the activity based on the data of the time period, and the scoring results are used to measure the workload of employees.

[0076] Among them, in step S51, the keyboard workload score formula is as follows:

[0077] When the comprehensive click volume C is lower than the reference value A:

[0078]

[0079] The maximum score does not exceed 100 points;

[0080] When the comprehensive click volume C is between the reference value A and the upper limit K:

[0081]

[0082] The maximum score does not exceed 100 points;

[0083] When the comprehensive click volume C exceeds the upper limit K:

[0084] B = 99.999;

[0085] Set parameters:

[0086] Among them, C is the comprehensive click volume, A is the preset reference average value of keyboard clicks, K is the upper limit of keyboard clicks, and K = A × 2. The result B is the keyboard workload score.

[0087] Among them, in step S51, the specific steps for the comprehensive workload score of the keyboard and mouse are as follows:

[0088] S511. First, calculate the comprehensive click volume;

[0089] S512. Calculate the workload score by calling the scoring function;

[0090] S513. Obtain the final comprehensive workload score of the keyboard and mouse.

[0091] Among them, in step S511, the calculation formula for the comprehensive click volume is:

[0092] C = K × W K + M × W M ;

[0093] In step S512, the calculation formula for the workload score is:

[0094] B Z = C × A;

[0095] In step S513, the final calculation formula for the workload score is:

[0096] B Z = (K × W K + M × W M ) × A;

[0097] Among them, K is the number of keyboard clicks of the user during this time period, M is the number of mouse clicks of the user during this time period, W K is the keyboard click weight, W M is the mouse click weight, A is the preset benchmark average value of keyboard clicks, B Z is the comprehensive busyness score of the keyboard and mouse.

[0098] Query the mouse and keyboard click data within a specific time period. The system captures the user's operation behavior through SQL query and sorts it according to the time period to ensure the accuracy of the scoring analysis.

[0099] The overall steps of the SQL query are: obtain the keyboard and mouse click data of the user within a specific time period from the table and summarize them.

[0100] Its core algorithm logic:

[0101] 1. Work busyness detection

[0102] By monitoring the number of mouse clicks and keyboard inputs of online office workers within each fixed time period (such as 5 minutes), and combining the keyboard click weight (80%) and the mouse click weight (20%), the system calculates the comprehensive busyness score. The score is adjusted according to the degree to which the user's operation exceeds or is lower than the benchmark average value.

[0103] 2. Activity interval analysis

[0104] The system queries the keyboard and mouse operation data of a specific user by time period, sorts these data and analyzes the activity of the user within each time interval. The data for every 5 minutes are processed independently to accurately reflect the user's activity.

[0105] 3. Busyness score calculation

[0106] Combining the click counts of the mouse and keyboard activity, the system sums them up with weights and then calculates the score based on the average keyboard click count (benchmark value), with the highest score being 100 points.

[0107] Online Office Staff Management System Based on Real-time Monitoring, including: Shift Management Module, which is used to set the working hours of online office staff according to the company's needs, monitor the actual attendance of online office staff, and generate attendance reports; Front-end Client Module, which is used to collect the working status of online office staff in real time and send data regularly; Back-end Client Module, which is used to receive data, store the data in MySQL and MongoDB databases, and use Redis for caching at the same time; Real-time Monitoring Module, which is used to listen to the screenshots and video operations uploaded by the Front-end Client Module according to RocketMQ, and update the online status and the time of the last heartbeat packet of online office staff in a timely manner; Data Analysis Module, which is used to analyze data, generate visual charts and curves, and display them. This system adopts a front-end and back-end separation architecture. The front-end displays the working status of online office staff through a browser, and the Front-end Client Module is responsible for collecting the real-time data of online office staff. The back-end uses Java SpringBoot as the server-side framework, and MySQL and MongoDB are used to store the status and task data of online office staff respectively. MySQL is mainly used to store structured data, such as the basic information, attendance records, task details, etc. of online office staff; MongoDB is used to store unstructured data, such as videos, pictures and text records in the historical work process, and the daily shift details. WebSocket realizes the real-time data transmission between the front-end and the back-end, and RocketMQ listens to the operations of the Front-end Client Module to upload screenshots and videos to ensure the timely update of the online status and the time of the last heartbeat packet of online office staff. The system caches the commonly used real-time status data through Redis, reduces the frequent access to the database, and improves the query and response speed, especially to ensure performance optimization in high-concurrency scenarios.

[0108] During the working process of the system, the Front-end Client Module sends information such as desktop screenshots, desktop recordings, and running applications of online office staff to the microservice every 5 minutes. After receiving the information, the microservice stores it in MySQL or MongoDB, and then sends a rocketMQ message to notify other services to update the online status and record the last heartbeat time. When the manager views the historical work situation of online office staff, the system will automatically play the content of the current work process in the form of videos or pictures. Each time the result is cached in Redis during loading to reduce database access and improve the system response speed.

[0109] In the real-time monitoring module, the front-end client module uploads the keyboard and mouse activity data within 5 minutes every 5 minutes. After receiving the data, the microservice stores the data in MySQL. The Feixiangyou and system client maintain a long WebSocket connection for the live broadcast function. To ensure the stability of the connection, the client and the server maintain a long connection and periodically detect the connection status through a heartbeat mechanism. When the management staff views the live broadcast of online office workers through the system, the front-end client module uploads the current desktop screenshot to the cloud object storage and sends the desktop screenshot data packet to the server in real time through WebSocket. After receiving the data packet, the server forwards it to the front end of the system of the administrator who is watching. The front end parses the received data packet and displays it on the live broadcast interface.

[0110] In the data analysis module, the back-end client module receives the keyboard and mouse activity data of online office workers and calculates the work saturation and busyness in real time. At the same time, the system analyzes the received running application information and classifies it according to the application category. The analysis results are visualized through a JavaScript chart library (such as ECharts) to generate a work saturation chart, a busyness curve, and application usage data, and are displayed through the front-end interface to help managers understand the team's workload and application usage in real time. The data is stored in MySQL, and at the same time, the frequently used data is cached in Redis to reduce direct access to the database and improve the system's response speed and performance. The system dynamically generates a work busyness score by monitoring the keyboard and mouse operation frequencies of online office workers. The algorithm calculates the activity based on the data in a time period (such as every 5 minutes), and the scoring result is used to measure the workload of employees.

[0111] In the shift scheduling management module, the administrator can set the shift scheduling plan of online office workers through the platform. After the scheduling is completed, the system will automatically generate the tasks of the current schedule and notify the shift scheduling personnel to receive the shift information. The system generates an attendance report based on the actual attendance data and analyzes it in combination with the work saturation data to help managers reasonably adjust the schedule. Managers can view the shift scheduling status and task completion status of current online office workers in real time through the system to optimize the work arrangement. Moreover, the shift scheduling management module submits the check-in and check-out data through the start work and end work of the front-end client module. After receiving the data, the microservice stores it in MySQL. Managers query the historical attendance records and the attendance situation of the day of online office workers. Through the historical attendance records, managers can comprehensively grasp the attendance rules of online office workers and conduct effective management and assessment in combination with the attendance data of the day.

[0112] Among them, the data analysis module visualizes the work saturation chart, work busyness curve, and historical work process data through a JavaScript chart library for managers to view and analyze in real time. The backend client module uses MySQL as the main database to store the status data and task data of online office workers, MongoDB to store unstructured data such as videos and graphic records, and Redis to cache frequently used data to accelerate data access and improve the system response speed.

[0113] Embodiment 1

[0114] Taking the online office worker Zhao XX as an example, Zhao XX's daily work is monitored and data is collected in real time through the front-end client module. Zhao XX starts working through the front-end client module at 8:00 every morning. The system will automatically record his online information and send the data to the backend microservices. After receiving the data, the microservices store it in the MySQL database and cache the online information in Redis for subsequent quick query and processing.

[0115] During the work process, the front-end client module uploads Zhao XX's desktop screenshots, desktop recordings, running application information, and keyboard and mouse activity data to the server every 5 minutes. The backend microservices classify and store this data in MySQL and MongoDB, and at the same time send messages through RocketMQ to notify other services to update Zhao XX's online status and the last heartbeat packet time. Managers can view Zhao XX's work status in real time through the system and obtain his work progress and task execution status through the front-end interface.

[0116] When the manager views Zhao XX's work live broadcast on the system, the front-end client module uploads the current desktop screenshot to the cloud object storage and transmits the screenshot data packet to the server in real time through WebSocket. After receiving the data packet, the server immediately forwards it to the front end of the system, and the manager can view Zhao XX's work screen in real time on the front-end interface to understand his task execution progress and operation status.

[0117] During the work process, the data analysis module continuously receives and analyzes Zhao XX's keyboard and mouse activity data, calculates his current work saturation and work busyness. The analysis results are visualized through the ECharts chart library, and the generated saturation curve and busyness chart are displayed on the manager's interface to help the manager evaluate Zhao XX's workload and allocate and adjust tasks in a timely manner.

[0118] In addition, the work schedule plan for Zhao XX is also automatically generated by the system. The administrator sets his working hours through the platform and notifies Zhao XX to receive tasks through the system. The system will generate an attendance report based on Zhao XX's actual attendance data and, combined with the results of work saturation analysis, help managers reasonably arrange subsequent work schedules and task assignments.

[0119] At the end of each day's work, Zhao XX submits the offline clock-in information through the front-end client module. The system will record and store this information, and combine the attendance data of the day with the historical attendance data for analysis to generate a complete attendance report for managers to query. Through the query system, the administrator can view Zhao XX's historical attendance situation and comprehensively grasp his attendance pattern and work efficiency.

[0120] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An online office staff management method based on real-time monitoring, characterized in that: The specific usage steps are as follows: S1: Set the working hours of online office staff according to company needs, monitor their actual attendance, and generate attendance reports; S2: collect the working status of online office workers in real time and send data regularly; S3: Receives data and stores it in MySQL and MongoDB databases, while using Redis for caching; S4: Update the online status and last heartbeat packet time of the online office staff according to the screenshots and video operations uploaded by RocketMQ monitoring front-end client module; S5: Analyze the data, generate visual charts and curves, and display them.

2. The online office staff management method based on real-time monitoring according to claim 1 is characterized in that: In step S1, after the attendance report is generated, the attendance status of the real-time online office staff is used to provide feedback to human resources in combination with the work saturation and busyness data to optimize the office staff scheduling.

3. The online office staff management method based on real-time monitoring according to claim 1 is characterized in that: In step S2, the front-end client module maintains a long connection with the back-end client module according to WebSocket, and sends the work status of the online office personnel at regular intervals, and the work status includes but is not limited to online status, task progress, keyboard and mouse activities, and running application data.

4. The online office staff management method based on real-time monitoring according to claim 1 is characterized in that: The specific steps of S5 are: S51, dynamically calculating the work saturation and work busyness of online office workers according to their historical work data, real-time task progress, keyboard and mouse activity data, and application information; S52, generating a visual work saturation chart and a work busyness curve; S53. Display charts and curves in a visual interface.

5. The online office staff management method based on real-time monitoring according to claim 1 is characterized in that: In step S51, the method for detecting work busyness is: the system dynamically generates a keyboard work busyness score and a keyboard and mouse comprehensive busyness score based on the keyboard and mouse operation frequency of the online office personnel monitored. The algorithm calculates the activity based on the data of the time period, and the score result is used to measure the employee workload.

6. The online office staff management method based on real-time monitoring according to claim 1 is characterized in that: In step S51, the keyboard work busyness scoring formula is: When the total click volume C is lower than the benchmark value A: The maximum score shall not exceed 100 points; When the total click volume C is between the reference value A and the upper limit K: The maximum score shall not exceed 100 points; When the total click volume C exceeds the upper limit K: B＝99.999； Setting parameters: Among them, C is the comprehensive click volume, A is the preset benchmark mean of keyboard clicks, K is the upper limit of keyboard clicks, and K=A×2, and the result B is the keyboard work busyness score.

7. The online office staff management method based on real-time monitoring according to claim 1 is characterized in that: In step S51, the specific steps of scoring the comprehensive busyness of the keyboard and mouse are as follows: S511, first calculate the comprehensive click volume; S512, calculating the busyness score by calling the scoring function; S513: Obtain the final keyboard and mouse comprehensive busyness score.

8. The online office staff management method based on real-time monitoring according to claim 1 is characterized in that: In step S511, the calculation formula of the comprehensive click volume is: C=K×W K +M×W M ; In step S512, the calculation formula of the busyness score is: B Z =C×A; In step S513, the final calculation formula of the busyness score is: B Z =(K×W K +M×W M )×A; Where K is the number of keyboard clicks by the user in this time period, M is the number of mouse clicks by the user in this time period, and W K is the keyboard click weight, W M is the mouse click weight, A is the preset benchmark mean of keyboard clicks, and B is Z It is the combined busyness score of keyboard and mouse.

9. An online office staff management system based on real-time monitoring, applying the online office staff management method based on real-time monitoring as claimed in any one of claims 1 to 8, characterized in that: include: The shift management module is used to set the working hours of online office staff according to the company's needs, monitor the actual attendance of online office staff, and generate attendance reports; The front-end client module is used to collect the working status of online office workers in real time and send data regularly; Backend client module, used to receive data and store it in MySQL and MongoDB databases, and use Redis for caching; The real-time monitoring module is used to timely update the online status and last heartbeat packet time of online office personnel based on the screenshots and video operations uploaded by RocketMQ monitoring front-end client modules; The data analysis module is used to analyze data, generate visual charts and curves, and display them.

10. The online office personnel management system based on real-time monitoring according to claim 9 is characterized in that: The data analysis module uses a JavaScript chart library to visualize work saturation charts, work busyness curves and historical work process data for managers to view and analyze in real time. The back-end client module uses MySQL as the main database to store status data and task data of online office personnel, MongoDB is used to store unstructured data, such as video and graphic records, and Redis is used to cache commonly used data, accelerate data access, and improve system response speed.

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