Smart classroom comprehensive management and control system

Abstract

The invention discloses a smart classroom comprehensive management and control system, and the system comprises a user management module which is responsible for the account management function of teachers, students and administrators; the equipment management module is responsible for managing various hardware equipment in the classroom and realizing remote control and state monitoring of the hardware equipment; the teaching monitoring module is responsible for monitoring video, audio and environment data in a classroom in real time and supporting abnormal behavior detection and alarm; the network monitoring module is responsible for ensuring continuity and stability of data transmission by adopting a multi-path network transmission technology; the data analysis module is responsible for analyzing and processing the collected data; according to the invention, by analyzing data such as learning behaviors and classroom participation degree of students, more comprehensive student management support is provided for teachers, personalized management and service schemes are provided according to characteristics and requirements of the students, an anomaly detection mechanism is established, monitored abnormal data are analyzed and processed, and occurrence of false alarm and missing report is prevented.

Description

Technical Field

[0001] The present invention relates to the field of smart school technology, and in particular to a smart classroom comprehensive management and control system. Background Art

[0002] With the rapid development of cloud computing, the Internet of Things, next-generation internet, and mobile communication technologies, the informatization of education has become an irreversible trend. These emerging technologies are constantly spawning new technologies, products, new businesses, new methods, and new thinking, driving industrial upgrades and profoundly changing the development model of education. Educational informatization not only improves teaching quality but also promotes the balanced distribution of educational resources, providing strong support for achieving educational equity. Smart classroom systems can help schools develop more scientific teaching plans and resource allocation strategies, achieving optimal allocation of educational resources.

[0003] A search revealed a Chinese invention patent, CN112907412A, which discloses a smart school internet classroom management and control system, belonging to the field of smart school internet technology. The system comprises multiple internet classrooms, each of which contains its classroom ID, a classroom weight value β, and a local internet management and control system terminal. The terminal includes at least a first classroom status data transmitter for monitoring active monitoring reports and submitting active monitoring requests. The active monitoring report indicates whether a teacher or student in the local internet classroom has triggered the first classroom status data transmitter, thereby initiating an active monitoring request. The active monitoring request is used to notify the smart school internet classroom management and control system that it needs to proactively monitor the local classroom.

[0004] Compared with the existing technology, this invention patent with Chinese patent number CN112907412A sets up an Internet of Things management and control system terminal for the Internet classroom, and executes smart school Internet classroom management based on a request mechanism and monitoring processing, thereby achieving: 1. Analysis of management and control reporting requests based on an active monitoring and reporting mechanism; 2. Student flow management based on target object coloring of management samples; 3. By marking and focusing on key students, specific Internet classroom management efficiency indicators are given to execute weighted feedback of smart school Internet classroom management, monitoring and reporting processing responses; 4. A first wake-up module is introduced to comprehensively transmit data or requests, realize system comprehensive management, execute specific smart school Internet classroom management and placement, and comprehensively and efficiently improve the management and control processing efficiency and control refinement granularity of the smart school Internet classroom management system.

[0005] However, during the above use, the focus is mainly on the monitoring and management of students' physical locations, but there may be deficiencies in the in-depth management of students' actual learning behavior, classroom participation, etc. Therefore, a comprehensive management and control system for smart classrooms is proposed. Summary of the Invention

[0006] The core purpose of this invention is to make up for the shortcomings of the existing technology, especially the limitations of the current system which mainly focuses on monitoring and managing students' physical location, but ignores the comprehensive monitoring and management of students' actual learning behavior, classroom participation and other deep-level learning status, thereby innovatively proposing a smart classroom comprehensive management and control system.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] A smart classroom comprehensive management and control system, including:

[0009] User management module: responsible for account registration, login, authority allocation and other management functions for teachers, students and administrators;

[0010] Equipment management module: responsible for managing various hardware devices in the classroom, such as projectors, speakers, cameras, sensors, etc., and realizing remote control and status monitoring of hardware devices;

[0011] Teaching monitoring module: responsible for real-time monitoring of video, audio and environmental data in the classroom, supporting abnormal behavior detection and alarm;

[0012] Network monitoring module: responsible for adopting multi-path network transmission technology to ensure the continuity and stability of data transmission;

[0013] Data analysis module: responsible for analyzing and processing the collected data, generating teaching evaluation reports, student behavior analysis reports, etc.;

[0014] System maintenance module: provides system log viewing, configuration management and troubleshooting to ensure stable operation of the system;

[0015] Data security module: responsible for data security and privacy protection;

[0016] The device management module performs remote control and status monitoring of the device based on the user permissions provided by the user management module. The user management module provides user identity and permission information to the teaching monitoring module so that the monitoring module can identify and record the operating behaviors of different users. The user management module provides user behavior data to the data analysis module for analyzing user usage habits and needs. The device management module provides the real-time status and performance parameters of the device to the teaching monitoring module so that the monitoring module can monitor the operation of the equipment in the classroom in real time. The device management module provides the equipment usage data and fault data to the data analysis module for evaluating the equipment usage efficiency and failure rate. The teaching monitoring module provides the collected video, audio and environmental data to the data analysis module for analyzing teaching effectiveness and student behavior.

[0017] The above technical solution further includes:

[0018] Furthermore, the user management module includes a front-end interface, a back-end service, a user database and a role management unit. The front-end interface is responsible for providing an interactive interface, the back-end service is responsible for performing business logic processing (such as verifying user information, assigning permissions, etc.), the user database is responsible for storing user data, and the role management unit is responsible for storing and managing permission information of different roles. The user fills in the information on the front-end interface and submits it. The back-end service receives the data and verifies it (such as checking whether the user name already exists). After the verification is passed, the data is stored in the user database and a unique identity (such as a user ID) is generated. The administrator assigns permissions to different roles (such as teachers, students, administrators) through the front-end interface. The permission information is stored in the role management module and is associated with the user role information in the user database. When the user logs in to the system, the system will obtain the corresponding permissions from the role management module based on its role information and control the user's access and operation to system resources.

[0019] Furthermore, the device management module includes a device interface unit, an authentication and authorization unit, a device management database, a remote control unit, an operation log unit, a monitoring data acquisition unit, a data analysis unit, an alarm notification unit, a status display unit and a data management database. The device interface unit is responsible for defining and providing interface standards for communicating with various devices (such as serial ports, network protocols, etc.). The authentication and authorization unit authenticates and authorizes the connected devices to ensure that only legal devices can access the system. The device management database records the basic information of the accessed devices (such as device ID, type, location, access time, etc.). The remote control unit receives user instructions and converts them into control signals that can be recognized by the device. The operation log unit records the time, user, operation content and other information of each remote control operation. The monitoring data acquisition unit is responsible for obtaining information from the device. Real-time status data and performance parameters, the data analysis unit: processes and analyzes the collected data to determine whether the equipment is operating normally. When the equipment is abnormal or fails, the alarm notification unit sends an alarm notification to the user. The status display unit displays the real-time status of the equipment to the user. The data management database stores historical status data and alarm records. The equipment interface unit receives status data and performance parameters from the equipment and passes them to the monitoring data collection unit. The authentication and authorization unit queries the equipment management database to verify the equipment identity when the equipment is connected, and stores the newly connected equipment information in the equipment management database. The monitoring data collection unit collects equipment status data. After the data analysis unit processes the equipment status data, if an abnormality is found, it triggers the alarm notification unit to send an alarm. At the same time, the status display unit displays the real-time status. All data are stored in the data management database.

[0020] Furthermore, the teaching monitoring module includes a camera unit, a video processing unit, a microphone unit, an audio processing unit, a speech recognition and analysis unit, a sensor unit, a data acquisition and processing unit, a video and audio analysis unit, and an alarm unit. The camera unit is responsible for collecting video data in the classroom. The video processing unit encodes, decodes, compresses, and performs other processing on the video data to support multi-screen switching and video playback. The microphone unit is responsible for collecting audio data in the classroom. The audio processing unit performs denoising, enhancement, recognition, and other processing on the audio data. The speech recognition and analysis unit converts the processed audio data into text and analyzes it. The sensor unit includes a temperature sensor, a humidity sensor, a light sensor, etc., and is responsible for collecting environmental data. The data acquisition and processing unit collects, processes, and stores the environmental data collected by the sensor unit. The video and audio analysis unit combines video and audio data and uses a machine learning algorithm to detect abnormal behavior. When abnormal behavior is detected, the alarm unit triggers an alarm signal, which may include a sound alarm, a screen prompt, or sending a notification to relevant personnel.

[0021] The camera unit transmits video data to the video processing unit, and the processed video data is displayed to the user through the front-end interface. The microphone unit transmits audio data to the audio processing unit, and the processed audio data is then transmitted to the speech recognition and analysis unit for recognition and analysis. The processed audio data and the recognition and analysis data are displayed to the user through the front-end interface. The sensor unit transmits environmental data to the data acquisition and processing unit, and the processed environmental data is displayed to the user through the front-end interface. The video and audio analysis unit receives data from the video processing unit and the audio processing unit, detects abnormal behavior, and transmits the results to the alarm unit and the front-end interface for alarm and display.

[0022] Furthermore, the camera unit and the video processing unit are used for video monitoring, real-time monitoring of the video images in the classroom, and support multi-screen switching and video playback functions, which allow teachers or administrators to view the real-time situation in the classroom at any time, or review past teaching scenes. The microphone unit, the audio processing unit, and the voice recognition and analysis unit are used for audio monitoring, collecting sound signals in the classroom, and supporting voice recognition and voice analysis, which helps to capture classroom interactions, analyze teaching quality, and may be used for subsequent teaching evaluations. The sensor unit and the data acquisition and processing unit are used for environmental data monitoring, monitoring environmental data such as temperature, humidity, and light in the classroom to ensure that the teaching environment is comfortable and conducive to students' learning. The video and audio analysis unit and the alarm unit are used for abnormal behavior detection. Through video and audio analysis, they detect students' abnormal behaviors (such as dozing off, playing with mobile phones, etc.) and trigger alarms, which helps to correct students' bad behaviors in a timely manner and maintain classroom discipline.

[0023] Furthermore, the network monitoring module includes a path management unit, a data distribution unit, a fault detection unit, a redundant device unit, a redundant link unit, a fault switching unit, a monitoring data acquisition unit, a data analysis and alarm unit, an alarm notification unit, a data cache unit, a data request processing unit and a cache update unit. The path management unit is responsible for selecting and maintaining multiple transmission paths. The data distribution unit distributes data to different paths for transmission according to the instructions of the path management unit. The fault detection unit monitors the status of each path in real time and notifies the path management unit immediately once a fault is found. The redundant device unit is responsible for managing redundant network devices, including redundant switches, routers and other network devices. The redundant link unit provides an additional network connection path. When a fault is detected, the fault switching unit is responsible for automatically switching to the redundant device or link. The monitoring data acquisition unit is responsible for collecting various monitoring data in the network. The data analysis and alarm unit analyzes and processes the collected data and generates alarm information when an abnormality is found. The alarm notification unit notifies the operation and maintenance personnel of the alarm information by SMS, email, etc. The data cache unit is responsible for storing and managing local cache data. The data request processing unit processes data requests from the user management module and obtains data from the local cache or remote server as appropriate. The cache update unit is responsible for updating the local cache data periodically or according to specific conditions.

[0024] Furthermore, the fault detection unit sends the path status information to the path management unit, and the path management unit adjusts the transmission path according to the information and sends the new path information to the data distribution unit. The data distribution unit then reallocates the data transmission tasks according to the new path information. The path management unit, the data distribution unit and the fault detection unit work together to realize multi-path transmission. When a path fails, it can automatically switch to other paths to ensure the continuity of data transmission. The fault switching unit continuously monitors the status of network devices and links. Once a fault is found, it immediately starts the switching mechanism to switch the service traffic from the failed device or link to the redundant device or link. At the same time, the fault switching unit notifies the network management system of the switching status information for recording and auditing. The redundant device unit, the redundant link unit and the fault switching unit work together to realize network redundancy design. When a device or link fails, the redundant device or link can take over the work to ensure the continuous operation of the network. The monitoring data acquisition unit transmits the collected monitoring data to the data analysis and alarm unit for processing. The data analysis and alarm When an abnormality is found during the analysis process, the unit generates an alarm message and sends the alarm letter to the alarm notification unit for distribution. The alarm notification unit then sends the alarm message to the operation and maintenance personnel according to a preset notification method. The monitoring data acquisition unit, the data analysis and alarm unit, and the alarm notification unit work together to realize real-time monitoring and alarm, deploy a network monitoring system, and monitor the network status in real time. When the client initiates a data request, the data request processing unit first checks whether the required data exists in the local cache. If so, the data is returned to the client directly from the cache. If not, a request is made to the remote server and waits for a response. At the same time, the cache update unit obtains the latest data from the remote server regularly or according to specific conditions according to a preset strategy and updates it to the local cache. This can reduce network dependence and ensure the real-time nature of the data. The data cache unit, the data request processing unit, and the cache update unit work together to implement a local cache strategy. A local cache strategy is adopted for key data to reduce network dependence and improve system response speed. When the network fails or is delayed, the system can quickly obtain the required data from the local cache.

[0025] Furthermore, the data analysis module includes a data acquisition unit, a data storage unit, a data analysis unit, an algorithm optimization unit, a personalized recommendation unit and a report generation unit. The data acquisition unit is responsible for designing and implementing the data acquisition plan to ensure the integrity and accuracy of the data. The data storage unit is responsible for storing the collected data in a safe and reliable database for subsequent analysis. The data analysis unit is responsible for performing data analysis tasks, developing analysis models, and extracting valuable information. The algorithm optimization unit is responsible for continuously improving and optimizing the analysis algorithm to improve the accuracy and efficiency of the analysis. The personalized recommendation unit provides students with personalized learning resources and suggestions based on the analysis results. The report generation unit is responsible for converting the analysis results into a readable report format to ensure the accuracy and readability of the report. The data acquisition unit transmits the collected data to the data storage unit for storage. The data analysis unit obtains the required data from the data storage unit for analysis and processing. The data analysis unit transmits the analysis results to the report generation unit.

[0026] Furthermore, the data analysis unit analyzes the students' learning behavior data through K-means to identify key information such as students' learning habits, interests and difficulties. The specific steps are:

[0027] Data collection: Collect students’ learning behavior data;

[0028] Data preprocessing: Cleaning, denoising, formatting and other preprocessing work are performed on the collected data to ensure data quality and consistency;

[0029] Feature extraction: extract features from preprocessed data;

[0030] Initialization: Select K initial centroids c k (cluster centroids), the centroids can be randomly selected or selected by some heuristic method;

[0031] Assign clusters: For each data point x k , calculate its distance to all K centroids:

[0032]

[0033] Assign each data point to the cluster corresponding to the centroid closest to it;

[0034] Update the centroid: For each cluster, recalculate its centroid. The new centroid is the mean of all points in the cluster. Assume that cluster S k Contains n data points k , then the new center of mass is c' k :

[0035] Iteration: Repeatedly assign clusters and update centroids until a stopping condition is met (such as the change in centroid is less than a threshold, or the preset number of iterations is reached);

[0036] Result analysis: Analyze clustering results to identify different learning behavior patterns or groups, such as students' learning patterns, potential learning barriers, etc.

[0037] Furthermore, the personalized recommendation unit provides students with personalized learning resources and suggestions based on the analysis results, specifically in the following steps:

[0038] User profile construction: Based on the results of learning behavior analysis, construct a user profile of students, including interests, preferences, abilities, etc.;

[0039] Hybrid recommendation: using collaborative filtering and content-based recommendations based on user profiles;

[0040] Collaborative filtering:

[0041] Constructing a user-learning resource matrix: Based on the user's reading history and ratings, construct a user-learning resource interaction matrix. Assuming there are m users and n learning resources, the user-learning resource matrix R can be expressed as:

[0042]

[0043] Among them, r ij Indicates the rating or usage count of learning resource j by user i. If a user has never used the corresponding learning resource, the corresponding element can be set to 0 or left blank.

[0044] Calculate similarity: Calculate the similarity between users with common reading preferences or between learning resources with similar themes and content:

[0045]

[0046] Among them, I uv is the set of learning resources that both user u and user v have interacted with, r ui is the rating or some kind of metric value of user u on learning resource i, r vi is the rating or metric value of user v on learning resource i;

[0047] Generate recommendation list: Generate a recommendation list for the current user based on the historical similarity of similar users' learning resource usage;

[0048] Content base recommendation:

[0049] Feature matching: Match the feature vector of the user's reading preference with the feature vector of the learning resource and calculate the similarity:

[0050]

[0051] in, is the feature vector of user’s preference for using learning resources, is the feature vector of learning resources;

[0052] Rating prediction: Based on content similarity, predict users' potential interest or satisfaction with unused learning resources;

[0053] Generate a recommendation list: Based on the actual application scenario and data characteristics, assign different weights to collaborative filtering and content-based recommendations. The scoring results of collaborative filtering and content-based recommendations are weighted and summed to obtain the final recommendation score. Based on the final score, the highest-scoring result is selected as the recommendation result to generate a personalized learning resource or suggestion list.

[0054] Recommendation effectiveness evaluation: Evaluate recommendation effectiveness through user feedback or behavioral data, and continuously optimize the recommendation algorithm.

[0055] The present invention has the following beneficial effects:

[0056] 1. In the present invention, by analyzing students' learning behavior, classroom participation and other data, teachers are provided with more comprehensive student management support, and personalized management and service plans are provided according to students' characteristics and needs, focusing on students' personalized development.

[0057] 2. In the present invention, comprehensive analysis and judgment are carried out in combination with multiple data sources to improve the accuracy and reliability of monitoring results, establish an anomaly detection mechanism, further analyze and process the monitored abnormal data, and prevent the occurrence of false alarms and missed alarms.

[0058] 3. In the present invention, multi-path network transmission technology is adopted. When the main path fails, it automatically switches to the backup path to ensure the continuity and stability of data transmission, add redundant equipment and links in the network architecture, improve the fault tolerance of the network, reduce the impact of single point failures on the system, and adopt a local caching strategy for key data to reduce network dependence and improve system response speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 This is a system block diagram of a smart classroom comprehensive management and control system proposed by the present invention;

[0060] Figure 2 This is a flow chart of the data analysis unit in the present invention analyzing student learning behavior data through K-means. DETAILED DESCRIPTION

[0061] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0062] See also Figure 1-Figure 2 As shown, the present invention is a comprehensive management and control system for smart classrooms, including:

[0063] User management module: responsible for account registration, login, authority allocation and other management functions for teachers, students and administrators;

[0064] Equipment management module: responsible for managing various hardware devices in the classroom, such as projectors, speakers, cameras, sensors, etc., and realizing remote control and status monitoring of hardware devices;

[0065] Teaching monitoring module: responsible for real-time monitoring of video, audio and environmental data in the classroom, supporting abnormal behavior detection and alarm;

[0066] Network monitoring module: responsible for adopting multi-path network transmission technology to ensure the continuity and stability of data transmission;

[0067] Data analysis module: responsible for analyzing and processing the collected data, generating teaching evaluation reports, student behavior analysis reports, etc.;

[0068] System maintenance module: provides system log viewing, configuration management and troubleshooting to ensure stable operation of the system;

[0069] Data security module: responsible for data security and privacy protection;

[0070] The device management module performs remote control and status monitoring of the equipment based on the user permissions provided by the user management module. The user management module provides user identity and permission information to the teaching monitoring module so that the monitoring module can identify and record the operating behaviors of different users. The user management module provides user behavior data to the data analysis module for analyzing user usage habits and needs. The device management module provides the real-time status and performance parameters of the equipment to the teaching monitoring module so that the monitoring module can monitor the operation of the equipment in the classroom in real time. The device management module provides equipment usage data and fault data to the data analysis module for evaluating the equipment's usage efficiency and failure rate. The teaching monitoring module provides the collected video, audio and environmental data to the data analysis module for analyzing teaching effectiveness and student behavior.

[0071] The working principle of the smart classroom comprehensive management and control system proposed by the present invention is that users register accounts and log in to the system through the front-end interface. The system assigns corresponding permissions according to user roles. The administrator enters the device management module through the user management module to register and configure the hardware devices (such as projectors, speakers, etc.) in the classroom. Based on the permissions set in the user management module, the administrator assigns different users (such as teachers) control permissions for specific devices.

[0072] The teaching monitoring module automatically starts and begins monitoring the classroom's video, audio, and environmental data based on the user identity and permission information provided by the user management module. The monitoring module analyzes the video and audio streams in real time and combines them with environmental data (such as noise level and light intensity) to detect abnormal behavior. If an abnormality is detected (such as a student leaving their seat or making loud noises), an alarm is immediately triggered and the event is recorded.

[0073] The network monitoring module uses multi-path network transmission technology to ensure the continuity and stability of data transmission between the teaching monitoring module and other modules, monitor the network status, promptly discover and solve potential network problems, and ensure data transmission efficiency and quality;

[0074] The data analysis module receives user behavior data from the user management module, device usage data and fault data from the device management module, and video, audio, and environmental data from the teaching monitoring module. It analyzes and processes this data to generate teaching evaluation reports, student behavior analysis reports, and device usage efficiency evaluation reports. These reports are displayed to administrators and teachers through the system interface to help them understand teaching effectiveness, student behavior, and device status.

[0075] The system maintenance module provides system log viewing, configuration management, and troubleshooting to ensure the stable operation of the system. The data security module is responsible for data security and privacy protection.

[0076] In one embodiment, for the above-mentioned user management module, the user management module includes a front-end interface, a back-end service, a user database and a role management unit. The front-end interface is responsible for providing an interactive interface, the back-end service is responsible for business logic processing (such as verifying user information, assigning permissions, etc.), the user database is responsible for storing user data, and the role management unit is responsible for storing and managing permission information of different roles. The user fills in the information on the front-end interface and submits it. The back-end service receives the data and verifies it (such as checking whether the user name already exists). After the verification is passed, the data is stored in the user database and a unique identity (such as a user ID) is generated. The administrator assigns permissions to different roles (such as teachers, students, and administrators) through the front-end interface. The permission information is stored in the role management module and is associated with the user role information in the user database. When the user logs in to the system, the system will obtain the corresponding permissions from the role management module based on its role information, and control the user's access and operation to system resources.

[0077] In one embodiment, for the above-mentioned device management module, the device management module includes a device interface unit, an authentication and authorization unit, a device management database, a remote control unit, an operation log unit, a monitoring data acquisition unit, a data analysis unit, an alarm notification unit, a status display unit and a data management database. The device interface unit is responsible for defining and providing interface standards (such as serial ports, network protocols, etc.) for communicating with various devices. The authentication and authorization unit authenticates and authorizes the connected devices to ensure that only legal devices can access the system. The device management database records the basic information of the accessed devices (such as device ID, type, location, access time, etc.). The remote control unit receives user instructions and converts them into control signals that can be recognized by the device. The operation log unit records the time, user, operation content and other information of each remote control operation. The monitoring data acquisition unit is responsible for The unit is responsible for obtaining real-time status data and performance parameters from the device. The data analysis unit processes and analyzes the collected data to determine whether the device is operating normally. When the device is abnormal or fails, the alarm notification unit sends an alarm notification to the user. The status display unit displays the real-time status of the device to the user. The data management database stores historical status data and alarm records. The device interface unit receives status data and performance parameters from the device and passes them to the monitoring data acquisition unit. The authentication and authorization unit queries the device management database to verify the device identity when the device is connected, and stores the newly connected device information in the device management database. The monitoring data acquisition unit collects device status data. After the data analysis unit processes the device status data, if any abnormality is found, it triggers the alarm notification unit to send an alarm. At the same time, the status display unit displays the real-time status. All data are stored in the data management database.

[0078] In one embodiment, for the above-mentioned teaching monitoring module, the teaching monitoring module includes a camera unit, a video processing unit, a microphone unit, an audio processing unit, a speech recognition and analysis unit, a sensor unit, a data acquisition and processing unit, a video and audio analysis unit, and an alarm unit. The camera unit is responsible for collecting video data in the classroom. The video processing unit encodes, decodes, compresses, and other processes the video data to support multi-screen switching and video playback. The microphone unit is responsible for collecting audio data in the classroom. The audio processing unit performs denoising, enhancement, recognition, and other processing on the audio data. The speech recognition and analysis unit converts the processed audio data into text and analyzes it. The sensor unit includes a temperature sensor, a humidity sensor, a light sensor, etc., and is responsible for collecting environmental data. The data acquisition and processing unit collects, processes, and stores the environmental data collected by the sensor unit. The video and audio analysis unit combines video and audio data and uses a machine learning algorithm to detect abnormal behavior. When abnormal behavior is detected, the alarm unit triggers an alarm signal, which may include a sound alarm, a screen prompt, or sending a notification to relevant personnel.

[0079] The camera unit transmits video data to the video processing unit, and the processed video data is displayed to the user through the front-end interface. The microphone unit transmits audio data to the audio processing unit, and the processed audio data is then passed to the speech recognition and analysis unit for recognition and analysis. The processed audio data and the recognition and analysis data are displayed to the user through the front-end interface. The sensor unit transmits environmental data to the data acquisition and processing unit, and the processed environmental data is displayed to the user through the front-end interface. The video and audio analysis unit receives data from the video processing unit and the audio processing unit, detects abnormal behavior, and then passes the results to the alarm unit and the front-end interface for alarm and display.

[0080] In one embodiment, for the above-mentioned camera unit, the camera unit and the video processing unit are used for video monitoring, real-time monitoring of the video images in the classroom, and support multi-screen switching and video playback functions, which allow teachers or administrators to view the real-time situation in the classroom at any time, or review past teaching scenes. The microphone unit, the audio processing unit, and the voice recognition and analysis unit are used for audio monitoring, collecting sound signals in the classroom, and supporting voice recognition and voice analysis, which helps to capture classroom interactions, analyze teaching quality, and may be used for subsequent teaching evaluations. The sensor unit and the data acquisition and processing unit are used for environmental data monitoring, monitoring environmental data such as temperature, humidity, and light in the classroom to ensure that the teaching environment is comfortable and conducive to students' learning. The video and audio analysis unit and the alarm unit are used for abnormal behavior detection. Through video and audio analysis, abnormal behaviors of students (such as dozing off, playing with mobile phones, etc.) are detected and alarms are triggered, which helps to correct students' bad behaviors in a timely manner and maintain classroom discipline.

[0081] In one embodiment, the network monitoring module includes a path management unit, a data distribution unit, a fault detection unit, a redundant device unit, a redundant link unit, a fault switching unit, a monitoring data acquisition unit, a data analysis and alarm unit, an alarm notification unit, a data cache unit, a data request processing unit, and a cache update unit. The path management unit is responsible for selecting and maintaining multiple transmission paths. The data distribution unit distributes data to different paths for transmission according to the instructions of the path management unit. The fault detection unit monitors the status of each path in real time and immediately notifies the path management unit once a fault is found. The redundant device unit is responsible for managing redundant network devices, including redundant switches. , routers and other network devices, the redundant link unit provides an additional network connection path. When a fault is detected, the fault switching unit is responsible for automatically switching to the redundant device or link. The monitoring data acquisition unit is responsible for collecting various monitoring data in the network. The data analysis and alarm unit analyzes and processes the collected data and generates alarm information when an abnormality is found. The alarm notification unit notifies the operation and maintenance personnel of the alarm information by SMS, email, etc. The data cache unit is responsible for storing and managing local cache data. The data request processing unit processes data requests from the user management module and obtains data from the local cache or remote server as appropriate. The cache update unit is responsible for updating the local cache data periodically or according to specific conditions.

[0082] In one embodiment, for the above-mentioned fault detection unit, the fault detection unit sends path status information to the path management unit. The path management unit adjusts the transmission path according to this information and sends the new path information to the data distribution unit. The data distribution unit reallocates the data transmission task according to the new path information. The path management unit, the data distribution unit and the fault detection unit work together to realize multi-path transmission. When a path fails, it can automatically switch to other paths to ensure the continuity of data transmission. The fault switching unit continuously monitors the status of network devices and links. Once a fault is found, it immediately starts the switching mechanism to switch the service traffic from the failed device or link to the redundant device or link. At the same time, the fault switching unit notifies the network management system of the switching status information for recording and auditing. The redundant device unit, the redundant link unit and the fault switching unit work together to realize network redundancy design. When a device or link fails, the redundant device or link can take over the work to ensure the continuous operation of the network. The monitoring data acquisition unit transmits the collected monitoring data to the data analysis and alarm unit for processing. The data analysis unit sends the collected monitoring data to the data analysis and alarm unit for processing. When an anomaly is discovered during the analysis process, the analysis and alarm unit generates an alarm message and sends the alarm message to the alarm notification unit for distribution. The alarm notification unit then sends the alarm message to the operation and maintenance personnel according to the preset notification method. The monitoring data collection unit, the data analysis and alarm unit, and the alarm notification unit work together to achieve real-time monitoring and alarm. The network monitoring system is deployed to monitor the network status in real time. When the client initiates a data request, the data request processing unit first checks whether the required data exists in the local cache. If so, it returns the data to the client directly from the cache. If not, it initiates a request to the remote server and waits for a response. At the same time, the cache update unit obtains the latest data from the remote server regularly or according to specific conditions according to the preset strategy and updates it to the local cache. This can reduce network dependence and ensure data real-time performance. The data cache unit, the data request processing unit, and the cache update unit work together to implement the local caching strategy. The local caching strategy is adopted for key data to reduce network dependence and improve system response speed. When the network fails or is delayed, the system can quickly obtain the required data from the local cache.

[0083] In one embodiment, for the above-mentioned data analysis module, the data analysis module includes a data acquisition unit, a data storage unit, a data analysis unit, an algorithm optimization unit, a personalized recommendation unit and a report generation unit. The data acquisition unit is responsible for designing and implementing the data acquisition plan to ensure the integrity and accuracy of the data. The data storage unit is responsible for storing the collected data in a safe and reliable database for subsequent analysis and use. The data analysis unit is responsible for performing data analysis tasks, developing analysis models, and extracting valuable information. The algorithm optimization unit is responsible for continuously improving and optimizing the analysis algorithm to improve the accuracy and efficiency of the analysis. The personalized recommendation unit provides students with personalized learning resources and suggestions based on the analysis results. The report generation unit is responsible for converting the analysis results into a readable report format to ensure the accuracy and readability of the report. The data acquisition unit transmits the collected data to the data storage unit for storage. The data analysis unit obtains the required data from the data storage unit for analysis and processing. The data analysis unit transmits the analysis results to the report generation unit.

[0084] In one embodiment, the data analysis unit analyzes the student learning behavior data through K-means to identify key information such as the student's learning habits, interests, and difficulties. The specific steps are as follows:

[0085] Data collection: Collect students’ learning behavior data;

[0086] Data preprocessing: Cleaning, denoising, formatting and other preprocessing work are performed on the collected data to ensure data quality and consistency;

[0087] Feature extraction: extract features from preprocessed data;

[0088] Initialization: Select K initial centroids c k (cluster centroids), the centroids can be chosen randomly or by some heuristic method;

[0089] Assign clusters: For each data point x k , calculate its distance to all K centroids:

[0090]

[0091] Assign each data point to the cluster corresponding to the centroid closest to it;

[0092] Update the centroid: For each cluster, recalculate its centroid. The new centroid is the mean of all points in the cluster. Assume that cluster S k Contains n data points k , then the new center of mass is c' k :

[0093] Iteration: Repeatedly assign clusters and update centroids until a stopping condition is met (such as the change in centroid is less than a threshold, or the preset number of iterations is reached);

[0094] Result analysis: Analyze clustering results to identify different learning behavior patterns or groups, such as students' learning patterns, potential learning barriers, etc.

[0095] In one embodiment, the personalized recommendation unit provides students with personalized learning resources and suggestions based on the analysis results. Specifically, the steps are as follows:

[0096] User profile construction: Based on the results of learning behavior analysis, construct a user profile of students, including interests, preferences, abilities, etc.;

[0097] Hybrid recommendation: using collaborative filtering and content-based recommendations based on user profiles;

[0098] Collaborative filtering:

[0099] Constructing a user-learning resource matrix: Based on the user's reading history and ratings, construct a user-learning resource interaction matrix. Assuming there are m users and n learning resources, the user-learning resource matrix R can be expressed as:

[0100]

[0101] Among them, r ij Indicates the rating or usage count of learning resource j by user i. If a user has never used the corresponding learning resource, the corresponding element can be set to 0 or left blank.

[0102] Calculate similarity: Calculate the similarity between users with common reading preferences or between learning resources with similar themes and content:

[0103]

[0104] Among them, I uv is the set of learning resources that both user u and user v have interacted with, r ui is the rating or some kind of metric value of user u on learning resource i, r vi is the rating or metric value of user v on learning resource i;

[0105] Generate recommendation list: Generate a recommendation list for the current user based on the historical similarity of similar users' learning resource usage;

[0106] Content base recommendation:

[0107] Feature matching: Match the feature vector of the user's reading preference with the feature vector of the learning resource and calculate the similarity:

[0108]

[0109] in, is the feature vector of user’s preference for using learning resources, is the feature vector of learning resources;

[0110] Rating prediction: Based on content similarity, predict users' potential interest or satisfaction with unused learning resources;

[0111] Generate a recommendation list: Based on the actual application scenario and data characteristics, assign different weights to collaborative filtering and content-based recommendations. The scoring results of collaborative filtering and content-based recommendations are weighted and summed to obtain the final recommendation score. Based on the final score, the highest-scoring result is selected as the recommendation result to generate a personalized learning resource or suggestion list.

[0112] Recommendation effectiveness evaluation: Evaluate recommendation effectiveness through user feedback or behavioral data, and continuously optimize the recommendation algorithm.

[0113] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A smart classroom comprehensive management and control system, characterized by: include: User management module: responsible for the account management functions of teachers, students and administrators; Equipment management module: responsible for managing various hardware devices in the classroom and realizing remote control and status monitoring of hardware devices; Teaching monitoring module: responsible for real-time monitoring of video, audio and environmental data in the classroom, supporting abnormal behavior detection and alarm; Network monitoring module: responsible for adopting multi-path network transmission technology to ensure the continuity and stability of data transmission; Data analysis module: responsible for analyzing and processing the collected data; System maintenance module: provides system log viewing, configuration management and troubleshooting; Data security module: responsible for data security and privacy protection; The device management module performs remote control and status monitoring of the device based on the user permissions provided by the user management module. The user management module provides user identity and permission information to the teaching monitoring module. The user management module provides user behavior data to the data analysis module. The device management module provides the real-time status and performance parameters of the device to the teaching monitoring module. The device management module provides device usage data and fault data to the data analysis module. The teaching monitoring module provides the collected video, audio and environmental data to the data analysis module. The data analysis module analyzes students' learning behavior data through K-means to identify students' learning habits, interests and difficulties, and provide personalized management and service solutions.

2. A smart classroom comprehensive management and control system according to claim 1, characterized in that: The user management module includes a front-end interface, a back-end service, a user database and a role management unit. The front-end interface is responsible for providing an interactive interface, the back-end service is responsible for business logic processing, the user database is responsible for storing user data, and the role management unit is responsible for storing and managing the permission information of different roles. The user fills in the information on the front-end interface and submits it. The back-end service receives the data and verifies it. After the verification is passed, the data is stored in the user database and a unique identity is generated. The administrator assigns permissions to different roles through the front-end interface. The permission information is stored in the role management module and is associated with the user role information in the user database.

3. A smart classroom comprehensive management and control system according to claim 1, characterized in that: The device management module includes a device interface unit, an authentication and authorization unit, a device management database, a remote control unit, an operation log unit, a monitoring data acquisition unit, a data analysis unit, an alarm notification unit, a status display unit and a data management database. The device interface unit is responsible for defining and providing interface standards for communicating with various devices. The authentication and authorization unit authenticates and authorizes the connected devices. The device management database records the basic information of the connected devices. The remote control unit receives user instructions and converts them into control signals that can be recognized by the device. The operation log unit records information about each remote control operation. The monitoring data acquisition unit is responsible for obtaining real-time status data and performance parameters from the device. The data analysis unit performs The collected data is processed and analyzed to determine whether the equipment is operating normally. When the equipment is abnormal or fails, the alarm notification unit sends an alarm notification to the user, and the status display unit displays the real-time status of the equipment to the user. The data management database stores historical status data and alarm records. The equipment interface unit receives status data and performance parameters from the equipment and passes them to the monitoring data collection unit. The authentication and authorization unit queries the equipment management database to verify the identity of the equipment when the equipment is connected, and stores the newly connected equipment information in the equipment management database. The monitoring data collection unit collects equipment status data. After the data analysis unit processes the equipment status data, if any abnormality is found, it triggers the alarm notification unit to send an alarm, and the status display unit displays the real-time status.

4. A smart classroom comprehensive management and control system according to claim 2, characterized in that: The teaching monitoring module includes a camera unit, a video processing unit, a microphone unit, an audio processing unit, a speech recognition and analysis unit, a sensor unit, a data acquisition and processing unit, a video and audio analysis unit, and an alarm unit. The camera unit is responsible for collecting video data in the classroom, the video processing unit processes the video data, the microphone unit is responsible for collecting audio data in the classroom, the audio processing unit processes the audio data, the speech recognition and analysis unit converts the processed audio data into text and analyzes it, the sensor unit is responsible for collecting environmental data, the data acquisition and processing unit collects, processes and stores the environmental data collected by the sensor unit, the video and audio analysis unit combines video and audio data and uses a machine learning algorithm to detect abnormal behavior. When abnormal behavior is detected, the alarm unit triggers an alarm signal; The camera unit transmits video data to the video processing unit, and the processed video data is displayed to the user through the front-end interface. The microphone unit transmits audio data to the audio processing unit, and the processed audio data is then transmitted to the speech recognition and analysis unit for recognition and analysis. The processed audio data and the recognition and analysis data are displayed to the user through the front-end interface. The sensor unit transmits environmental data to the data acquisition and processing unit, and the processed environmental data is displayed to the user through the front-end interface. The video and audio analysis unit receives data from the video processing unit and the audio processing unit, detects abnormal behavior, and transmits the results to the alarm unit and the front-end interface for alarm and display.

5. A smart classroom comprehensive management and control system according to claim 4, characterized in that: The camera unit and video processing unit are used for video monitoring, the microphone unit, audio processing unit and speech recognition and analysis unit are used for audio monitoring, the sensor unit and data acquisition and processing unit are used for environmental data monitoring, and the video and audio analysis unit and alarm unit are used for abnormal behavior detection.

6. A smart classroom comprehensive management and control system according to claim 1, characterized in that: The network monitoring module includes a path management unit, a data distribution unit, a fault detection unit, a redundant device unit, a redundant link unit, a fault switching unit, a monitoring data acquisition unit, a data analysis and alarm unit, an alarm notification unit, a data cache unit, a data request processing unit and a cache update unit. The path management unit is responsible for selecting and maintaining multiple transmission paths. The data distribution unit distributes data to different paths for transmission according to the instructions of the path management unit. The fault detection unit monitors the status of each path in real time and notifies the path management unit immediately once a fault is found. The redundant device unit is responsible for managing redundant network devices. The redundant link unit is responsible for The element provides an additional network connection path. When a fault is detected, the fault switching unit is responsible for automatically switching to a redundant device or link. The monitoring data acquisition unit is responsible for collecting various monitoring data in the network. The data analysis and alarm unit analyzes and processes the collected data and generates alarm information when an abnormality is found. The alarm notification unit notifies the operation and maintenance personnel of the alarm information. The data cache unit is responsible for storing and managing local cache data. The data request processing unit processes data requests from the user management module and obtains data from the local cache or remote server as appropriate. The cache update unit is responsible for updating the local cache data periodically or according to specific conditions.

7. A smart classroom integrated management and control system according to claim 6, characterized in that: The fault detection unit sends the path status information to the path management unit, and the path management unit adjusts the transmission path according to the information and sends the new path information to the data distribution unit. The data distribution unit then reallocates the data transmission tasks according to the new path information. The path management unit, the data distribution unit and the fault detection unit work together to realize multi-path transmission. The fault switching unit continuously monitors the status of network devices and links, and immediately starts the switching mechanism once a fault is found, switching the service traffic from the faulty device or link to the redundant device or link. The redundant device unit, the redundant link unit and the fault switching unit work together to realize network redundancy design. The monitoring data acquisition unit transmits the collected monitoring data to the data analysis and alarm unit. The data analysis and alarm unit generates an alarm message when an abnormality is found during the analysis process, and sends the alarm message to the alarm notification unit for distribution. The alarm notification unit sends the alarm message to the operation and maintenance personnel according to the preset notification method. The monitoring data acquisition unit, the data analysis and alarm unit and the alarm notification unit work together to realize real-time monitoring and alarm. When the client initiates a data request, the data request processing unit first checks whether the required data exists in the local cache. At the same time, the cache update unit obtains the latest data from the remote server regularly according to the preset strategy or according to specific conditions and updates it to the local cache. The data cache unit, the data request processing unit and the cache update unit work together to realize the local cache strategy.

8. The smart classroom integrated management and control system according to claim 1, characterized in that: The data analysis module includes a data acquisition unit, a data storage unit, a data analysis unit, an algorithm optimization unit, a personalized recommendation unit and a report generation unit. The data acquisition unit is responsible for designing and implementing the data acquisition plan, the data storage unit is responsible for storing the collected data in the database, the data analysis unit is responsible for performing data analysis tasks, developing analysis models, and extracting valuable information, the algorithm optimization unit is responsible for continuously improving and optimizing the analysis algorithm, the personalized recommendation unit provides students with personalized learning resources and suggestions based on the analysis results, the report generation unit is responsible for converting the analysis results into a readable report format, the data acquisition unit transmits the collected data to the data storage unit for storage, the data analysis unit obtains the required data from the data storage unit for analysis and processing, and the data analysis unit transmits the analysis results to the report generation unit.

9. A smart classroom integrated management and control system according to claim 8, characterized in that: The data analysis unit analyzes the student learning behavior data through K-means, specifically the following steps: Data collection: Collect students’ learning behavior data; Data preprocessing: preprocess the collected data; Feature extraction: extract features from preprocessed data; Initialization: Select K initial centroids c k ; Assign clusters: For each data point x k , calculate its distance to all K centroids: Assign each data point to the cluster corresponding to the centroid closest to it; Update the centroid: For each cluster, recalculate its centroid. The new centroid is the mean of all points in the cluster. Assume that cluster S k Contains n data points k , then the new center of mass is c, k : Iteration: Repeatedly assign clusters and update centroids until a stopping condition is met; Result analysis: Analyze clustering results to identify different learning behavior patterns or groups.

10. A smart classroom integrated management and control system according to claim 8, characterized in that: The personalized recommendation unit provides students with personalized learning resources and suggestions based on the analysis results. The specific steps are as follows: User portrait construction: Build student user portraits based on learning behavior analysis results; Hybrid recommendation: using collaborative filtering and content-based recommendations based on user profiles; Generate a recommendation list: Based on the actual application scenario and data characteristics, assign different weights to collaborative filtering and content-based recommendations. The scoring results of collaborative filtering and content-based recommendations are weighted and summed to obtain the final recommendation score. Based on the final score, the highest-scoring result is selected as the recommendation result to generate a personalized learning resource or suggestion list. Recommendation effectiveness evaluation: Evaluate recommendation effectiveness through user feedback or behavioral data, and continuously optimize the recommendation algorithm.

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