Smart classroom remote monitoring method and system

Abstract

The invention relates to the technical field of smart classroom supervision, and particularly discloses a smart classroom remote monitoring method and system, and the method comprises the steps: analyzing the state of a smart classroom remote monitoring communication link, judging whether the state of the smart classroom remote monitoring communication link is qualified or not, analyzing the basic information of a smart classroom, and judging whether the state of the smart classroom remote monitoring communication link is qualified or not; comparing to obtain an intelligent classroom remote monitoring scheme, analyzing a classroom teaching state, judging whether the classroom teaching state is qualified or not, analyzing a classroom audio state, judging whether the classroom audio state is qualified or not, analyzing a classroom student learning behavior state, and judging whether the classroom student learning behavior state is qualified or not; according to the invention, the problem that the traditional teaching mode usually depends on homework and examination after class to evaluate the learning effect of students and subjective judgment of teachers and lacks timely learning state feedback is solved, the instantaneity and effectiveness of classroom teaching are improved, and the improvement of the overall teaching quality is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of smart classroom supervision, and in particular to a smart classroom remote monitoring method and system. Background Art

[0002] With the rapid development of technologies such as the Internet, the Internet of Things, big data, and artificial intelligence, the education industry is gradually realizing informatization and intelligence. Smart classrooms are an important part of educational informatization, aiming to improve teaching quality and efficiency through modern technical means. The application of artificial intelligence technology in education is becoming more and more extensive. Through big data analysis, students' learning status can be monitored and evaluated in a timely manner to provide support for personalized teaching. The development of sensors and Internet of Things technologies has made it possible to monitor classroom environment and student behavior, providing a rich source of information for smart classroom systems. Distance learning has become one of the main modes of the global education system. The smart classroom remote monitoring system can ensure the effective management of classroom order and teaching effectiveness during distance learning, making up for the shortcomings caused by the absence of physical classrooms.

[0003] For example, the invention patent with publication number CN116629488A discloses a remote monitoring method and system for a smart classroom, wherein the method includes: obtaining classroom monitoring information; classifying the classroom monitoring information to obtain multiple sub-monitoring information; sending the sub-monitoring information to the corresponding preset module to obtain the scoring information of the corresponding sub-monitoring information; judging whether the score of the sub-monitoring information is lower than the corresponding preset scoring threshold, if so, sending the scoring information of the corresponding sub-monitoring information to the corresponding preset management terminal for display; if not, not sending it. The present invention automatically extracts teachers or students who perform poorly in class through a scoring system, and sends the information of teachers or students who perform poorly to the corresponding management terminal for display. The present invention also records the teacher's monitoring information into a teaching video, which is convenient for students to watch repeatedly and strengthen students' consolidation of knowledge points.

[0004] Nowadays, there are still some shortcomings in the research on a remote monitoring method for smart classrooms. Specifically, in traditional classrooms, it is difficult for teachers to pay attention to the learning status of all students at the same time. Traditional teaching methods usually rely on after-class homework and exams to evaluate students' learning effects and rely on teachers' subjective judgments. There is a lack of timely feedback on learning status. In traditional classrooms, teachers' attention is often focused on a small number of actively participating students, while those who are less active or have learning difficulties are easily ignored. This may lead to the failure to discover and solve these students' learning problems in a timely manner, ultimately affecting students' learning effects and enthusiasm. In addition, after-class evaluation has a lag, and different teachers may have differences in scoring standards and teaching evaluations, which makes the evaluation of students' learning effects lack consistency and affects the fairness and scientificity of teaching. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a smart classroom remote monitoring method and system, which can effectively solve the problems involved in the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: In a first aspect, the present invention provides a smart classroom remote monitoring method, comprising the following steps: analyzing the status of a smart classroom remote monitoring communication link to determine whether the status of the smart classroom remote monitoring communication link is qualified; analyzing the basic information of the smart classroom, and comparing to obtain a smart classroom remote monitoring plan, wherein the smart classroom remote monitoring plan specifically includes a classroom teaching status acquisition frequency, a classroom audio status acquisition frequency, and a classroom student learning behavior status acquisition frequency; based on the classroom teaching status acquisition frequency, analyzing the classroom teaching status of a qualified smart classroom remote monitoring communication link to determine whether the classroom teaching status is qualified; based on the classroom audio status acquisition frequency, analyzing the classroom audio status of a qualified smart classroom remote monitoring communication link to determine whether the classroom audio status is qualified; based on the classroom student learning behavior status acquisition frequency, analyzing the classroom student learning behavior status of a qualified smart classroom remote monitoring communication link to determine whether the classroom student learning behavior status is qualified.

[0007] As a further method, it is determined whether the state of the smart classroom remote monitoring communication link is qualified. The specific analysis process is as follows: the smart classroom remote monitoring communication link state is analyzed to obtain a data set of the smart classroom remote monitoring communication link state. The smart classroom remote monitoring communication link state specifically includes the communication link transmission delay, the communication link network bandwidth, and the communication link packet loss rate; based on the obtained data set of the smart classroom remote monitoring communication link state, a comprehensive analysis is performed to obtain an evaluation value of the smart classroom remote monitoring communication link state. The evaluation value of the smart classroom remote monitoring communication link state is used as an analysis basis for determining whether the state of the smart classroom remote monitoring communication link is qualified; the evaluation value of the smart classroom remote monitoring communication link state is compared with a reference evaluation value of the smart classroom remote monitoring communication link state stored in a database; if the evaluation value of the smart classroom remote monitoring communication link state is higher than or equal to the reference evaluation value of the smart classroom remote monitoring communication link state, the smart classroom remote monitoring communication link state corresponding to the evaluation value of the smart classroom remote monitoring communication link state is qualified; if the evaluation value of the smart classroom remote monitoring communication link state is lower than the reference evaluation value of the smart classroom remote monitoring communication link state, the smart classroom remote monitoring communication link state corresponding to the evaluation value of the smart classroom remote monitoring communication link state is unqualified, and the unqualified smart classroom remote monitoring communication link is replaced.

[0008] As a further method, a remote monitoring plan for a smart classroom is obtained by comparison. The specific analysis process is as follows: the basic information of the smart classroom is analyzed to obtain a basic information data set of the smart classroom. The basic information data set of the smart classroom specifically includes the frequency of classes, the length of each class, and the number of students in the class; the frequency of classes, the length of each class, and the number of students in the class are stored as designated tags, and the designated tags are compared with the remote monitoring plans for the smart classroom corresponding to the designated tags stored in the database to obtain the remote monitoring plan for the smart classroom corresponding to the designated tags.

[0009] As a further method, whether the classroom teaching status is qualified is judged. The specific analysis process is: based on the classroom teaching status acquisition frequency, the classroom teaching status of the smart classroom remote monitoring communication link with a qualified status is analyzed to obtain a classroom teaching status data set, and the classroom teaching status data set specifically includes the teacher-student interaction frequency, student attendance rate, and teacher blackboard area; based on the obtained classroom teaching status data set, a comprehensive analysis is performed to obtain a classroom teaching status evaluation value, and the classroom teaching status evaluation value is used as an analysis basis for judging whether the classroom teaching status is qualified; the classroom teaching status evaluation value is compared with the classroom teaching status reference evaluation value stored in the database; if the classroom teaching status evaluation value is higher than or equal to the classroom teaching status reference evaluation value, the classroom teaching status corresponding to the classroom teaching status evaluation value is qualified; if the classroom teaching status evaluation value is lower than the classroom teaching status reference evaluation value, the classroom teaching status corresponding to the classroom teaching status evaluation value is unqualified, and an alarm prompt is issued for the unqualified classroom teaching status.

[0010] As a further method, the classroom teaching status evaluation value, the specific analysis process is: ; In the formula, is the classroom teaching status evaluation value, The frequency of teacher-student interaction, For student attendance, The area for teachers to write on the blackboard. is the compensation factor for the set teacher-student interaction frequency, is the compensation factor for the set student attendance rate, It is the compensation factor for the set blackboard writing area of ​​the teacher.

[0011] As a further method, whether the classroom audio status is qualified is judged. The specific analysis process is: based on the classroom audio status acquisition frequency, the classroom audio status of the smart classroom remote monitoring communication link with a qualified status is analyzed to obtain a classroom audio status data set. The classroom audio status data set specifically includes the absolute value of the difference between the teacher's speaking speed and the reference speaking speed, the classroom noise decibel value, and the proportion of the teacher's speaking time; based on the obtained classroom audio status data set, a comprehensive analysis is performed to obtain a classroom audio status evaluation value, and the classroom audio status evaluation value is used as an analysis basis for judging whether the classroom audio status is qualified; the classroom audio status evaluation value is compared with the classroom audio status reference evaluation value stored in the database; if the classroom audio status evaluation value is higher than or equal to the classroom audio status reference evaluation value, the classroom audio status corresponding to the classroom audio status evaluation value is qualified; if the classroom audio status evaluation value is lower than the classroom audio status reference evaluation value, the classroom audio status corresponding to the classroom audio status evaluation value is unqualified, and an alarm prompt is issued for the unqualified classroom audio status.

[0012] As a further method, the classroom audio status evaluation value, the specific analysis process is: ; In the formula, is the classroom audio status evaluation value, is the absolute value of the difference between the teacher's speaking speed and the reference speaking speed, is the decibel value of classroom noise, The proportion of teachers' speaking time, is the compensation factor for the absolute value of the difference between the teacher's speaking speed and the reference speaking speed. is the compensation factor for the set classroom noise decibel value, is the compensation factor for the proportion of teacher’s speaking time, and e is a natural constant.

[0013] As a further method, it is judged whether the learning behavior status of classroom students is qualified. The specific analysis process is: based on the frequency of classroom student learning behavior status collection, the classroom student learning behavior status of the smart classroom remote monitoring communication link with qualified status is analyzed to obtain the classroom student learning behavior status data set; based on the obtained classroom student learning behavior status data set, a comprehensive analysis is performed to obtain a classroom student learning behavior status evaluation value, and the classroom student learning behavior status evaluation value is used as an analysis basis for judging whether the classroom student learning behavior status is qualified; the classroom student learning behavior status evaluation value is compared with the classroom student learning behavior status reference evaluation value stored in the database; if the classroom student learning behavior status evaluation value is higher than or equal to the classroom student learning behavior status reference evaluation value, then the classroom student learning behavior status corresponding to the classroom student learning behavior status evaluation value is qualified; if the classroom student learning behavior status evaluation value is lower than the classroom student learning behavior status reference evaluation value, then the classroom student learning behavior status corresponding to the classroom student learning behavior status evaluation value is unqualified, and an alarm prompt is issued for the unqualified classroom student learning behavior status.

[0014] As a further method, a dataset of students’ learning behavior status in the classroom is used, which specifically includes the frequency of students’ head movements, the frequency of students’ eye movements, and the angle between students’ sitting posture and the plumb plane.

[0015] The second aspect of the present invention provides a smart classroom remote monitoring system, including a communication link status judgment module, a remote monitoring scheme comparison module, a classroom teaching status judgment module, a classroom audio status judgment module and a student learning behavior status judgment module, wherein: the communication link status judgment module is used to analyze the status of the smart classroom remote monitoring communication link to determine whether the status of the smart classroom remote monitoring communication link is qualified; the remote monitoring scheme comparison module is used to analyze the basic information of the smart classroom and compare to obtain the smart classroom remote monitoring scheme, the smart classroom remote monitoring scheme specifically includes the classroom teaching status acquisition frequency, the classroom audio status acquisition frequency, the classroom student learning behavior The classroom teaching status judgment module is used to analyze the classroom teaching status of the smart classroom remote monitoring communication link with a qualified status based on the classroom teaching status collection frequency, and judge whether the classroom teaching status is qualified; the classroom audio status judgment module is used to analyze the classroom audio status of the smart classroom remote monitoring communication link with a qualified status based on the classroom audio status collection frequency, and judge whether the classroom audio status is qualified; the student learning behavior status judgment module is used to analyze the classroom student learning behavior status of the smart classroom remote monitoring communication link with a qualified status based on the classroom student learning behavior status collection frequency, and judge whether the classroom student learning behavior status is qualified.

[0016] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention provides a smart classroom remote monitoring method and system. Through data collection and analysis at an appropriate frequency, the classroom teaching status, audio status and the eligibility of students' learning behavior can be quickly judged. This timely monitoring allows teachers to quickly understand the teaching progress in the classroom, discover and correct possible problems in a timely manner, thereby improving the immediacy and effectiveness of classroom teaching. Multi-level monitoring and analysis can help education administrators obtain detailed classroom information, evaluate teachers' teaching performance and students' learning effects, and promote the improvement of overall teaching quality.

[0017] (2) The present invention analyzes the basic information of the smart classroom and obtains the remote monitoring plan of the smart classroom by comparison. By analyzing the basic information of the smart classroom, the remote monitoring plan can be tailored according to specific needs. This customized plan can better adapt to different types of classrooms and teaching modes, ensuring the effectiveness and practicality of the monitoring system. Through comparison and analysis, the specific needs of different classrooms can be accurately identified, and the monitoring plan can be optimized according to these needs. The monitoring plan can be more flexible and adapt to different classroom environments and changing teaching requirements. The monitoring strategy and collection frequency can be adjusted according to the data to ensure the continuous optimization of the monitoring effect.

[0018] (3) The present invention analyzes the classroom teaching status, classroom audio status, and classroom student learning behavior status. By analyzing the classroom teaching status, audio status, and student learning behavior status, the present invention can comprehensively understand the classroom teaching effect from multiple angles. The teaching status analysis can reveal the delivery effect of the teaching content. The audio status analysis can ensure the clear communication of information. The learning behavior status analysis can evaluate the student participation and understanding. The multi-dimensional data analysis can help teachers and education managers discover specific problems in the classroom, such as too fast teaching pace, unclear audio, and lack of student concentration, so as to make precise improvements and continuously optimize the teaching methods, thereby improving the overall teaching quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0020] Figure 1 The figure is a schematic flow chart of the method steps of the present invention.

[0021] Figure 2 It is a schematic diagram of system module connection of the present invention. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0023] Reference Figure 1 As shown, the first aspect of the present invention provides a smart classroom remote monitoring method, including: analyzing the state of the smart classroom remote monitoring communication link, and judging whether the state of the smart classroom remote monitoring communication link is qualified.

[0024] Specifically, it is determined whether the status of the remote monitoring communication link of the smart classroom is qualified. The specific analysis process is as follows: analyze the status of the remote monitoring communication link of the smart classroom, and obtain the data set of the remote monitoring communication link status of the smart classroom. The remote monitoring communication link status of the smart classroom specifically includes the communication link transmission delay, the communication link network bandwidth, and the communication link packet loss rate. The communication link transmission delay, also known as delay, refers to the time required for data to be transmitted from the sender to the receiver. The communication link network bandwidth refers to the maximum amount of data that can be transmitted by the communication link per unit time. The communication link packet loss rate refers to the proportion of data packets sent on the communication link that fail to successfully reach the destination, usually expressed as a percentage. The communication link transmission delay, the communication link network bandwidth, and the communication link packet loss rate are obtained through network monitoring tools and router / switch logs; based on the obtained data set of the remote monitoring communication link status of the smart classroom, A comprehensive analysis is performed to obtain an evaluation value of the state of the remote monitoring communication link of the smart classroom, and the evaluation value of the state of the remote monitoring communication link of the smart classroom is used as an analysis basis for judging whether the state of the remote monitoring communication link of the smart classroom is qualified; the evaluation value of the state of the remote monitoring communication link of the smart classroom is compared with a reference evaluation value of the state of the remote monitoring communication link of the smart classroom stored in the database; if the evaluation value of the state of the remote monitoring communication link of the smart classroom is higher than or equal to the reference evaluation value of the state of the remote monitoring communication link of the smart classroom, the state of the remote monitoring communication link of the smart classroom corresponding to the evaluation value of the state of the remote monitoring communication link of the smart classroom is qualified; if the evaluation value of the state of the remote monitoring communication link of the smart classroom is lower than the reference evaluation value of the state of the remote monitoring communication link of the smart classroom, the state of the remote monitoring communication link of the smart classroom corresponding to the evaluation value of the state of the remote monitoring communication link of the smart classroom is unqualified, and the unqualified remote monitoring communication link of the smart classroom is replaced.

[0025] In a specific embodiment, if the network bandwidth is high and the latency is large, the amount of data maintained in the network will be larger, which means that even if the bandwidth is high, if the latency is large, the actual throughput of data transmission may be limited. When the network packet loss rate is high, the transport layer protocol (such as TCP) will usually trigger the retransmission of data packets, resulting in an increase in the overall transmission delay. Each packet loss will extend the time it takes for data to reach the receiving end, especially when multiple retransmissions are required, the latency may increase significantly. When the network bandwidth is close to saturation, especially when the bandwidth utilization reaches its peak, the buffers of network devices (such as routers and switches) may overflow, causing data packets to be discarded, which in turn causes an increase in the packet loss rate. The packet loss rate tends to increase when the bandwidth is insufficient or the network is overloaded.

[0026] In a specific embodiment, analyzing the transmission delay of the communication link and replacing the unqualified link can significantly reduce the delay of data transmission, which is crucial to the monitoring system. It can ensure that the classroom video, audio and data can be transmitted in time and ensure the smoothness of monitoring. Timely teaching status feedback is an important part of the smart classroom. By reducing the communication delay, it can ensure that the monitoring system can respond quickly and provide timely feedback, thereby supporting teachers to make timely adjustments in the classroom and improve teaching effectiveness. The network bandwidth of the communication link is analyzed to ensure that it can meet the needs of the smart classroom system. If the bandwidth is insufficient, it may cause a bottleneck in data transmission, affecting the quality of the audio and video streams and the integrity of the data. Replacing the link with insufficient bandwidth can improve the stability of the overall data transmission and ensure the reliable operation of the system. Analyzing the packet loss rate of the communication link and replacing the unqualified link can effectively reduce the loss of data packets during the transmission process, which is crucial to ensuring the integrity of the monitoring data, especially when transmitting key classroom videos and student behavior data. Data packet loss may lead to missing or misunderstanding of information. Unqualified communication links are prone to communication failures, affecting the normal operation of the system. By replacing these links, the probability of communication failures can be greatly reduced, and the reliability of the entire smart classroom system can be improved.

[0027] In a specific embodiment, the specific analysis process of the smart classroom remote monitoring communication link status evaluation value is as follows: ; In the formula, It is the evaluation value of the communication link status of the smart classroom remote monitoring. is the transmission delay of the communication link, is the communication link network bandwidth, is the communication link packet loss rate, is the compensation factor of the transmission delay of the communication link, is the compensation factor for the set communication link network bandwidth, is the compensation factor for the packet loss rate of the set communication link.

[0028] It needs to be explained that the above-mentioned smart classroom remote monitoring communication link status evaluation value is calculated through the communication link transmission delay, communication link network bandwidth, and communication link packet loss rate. The communication link transmission delay, communication link network bandwidth, and communication link packet loss rate are normalized. The communication link transmission delay, network bandwidth, and packet loss rate represent different aspects of network performance. By combining these indicators, the overall status of the network can be comprehensively evaluated, so as to accurately judge whether the communication link is suitable for smart classroom remote monitoring. This multi-dimensional evaluation can better reflect the actual use of the network than a single indicator. The calculated communication link status evaluation value can help identify potential network problems, such as high latency, low bandwidth, or high packet loss rate. These problems will affect the stable transmission of data. By monitoring these indicators, the system can promptly discover and handle network problems, ensure the stability and continuity of monitoring data, effectively monitor network packet loss rate and transmission delay, ensure the integrity of monitoring video, audio and data streams, and reduce the decline in monitoring effect due to data loss or transmission delay. , , It is the compensation factor corresponding to the communication link transmission delay, communication link network bandwidth, and communication link packet loss rate preset in the database, which represents the numerical value of the influence of the communication link transmission delay, communication link network bandwidth, and communication link packet loss rate on the evaluation value of the communication link status of the smart classroom remote monitoring. When used, the compensation factor corresponding to the communication link transmission delay, communication link network bandwidth, and communication link packet loss rate can be directly obtained from the database, and the corresponding relationship can be a preset mapping relationship. For example, the communication link transmission delay, communication link network bandwidth, and communication link packet loss rate are formed with the compensation factors of the communication link transmission delay, communication link network bandwidth, and communication link packet loss rate preset in the database to form a mapping set, and the real-time communication link transmission delay, communication link network bandwidth, and communication link packet loss rate are input into the mapping set to obtain the compensation factors corresponding to the communication link transmission delay, communication link network bandwidth, and communication link packet loss rate. The mapping relationship can be one-to-one or many-to-one.

[0029] The basic information of the smart classroom is analyzed and compared to obtain the remote monitoring plan of the smart classroom. The remote monitoring plan of the smart classroom specifically includes the frequency of collecting classroom teaching status, the frequency of collecting classroom audio status, and the frequency of collecting classroom student learning behavior status.

[0030] Specifically, the comparison obtains the remote monitoring scheme of the smart classroom, and the specific analysis process is: analyze the basic information of the smart classroom to obtain the basic information data set of the smart classroom, the basic information data set of the smart classroom specifically includes the frequency of course opening, the class duration of each class, and the number of students in the class. The frequency of course opening indicates the frequency of course teaching, which is usually obtained through the learning management system, the academic affairs management system or the course schedule data. The class duration of each class in the class indicates the duration of each teaching, which is usually obtained through the course management system, the scheduling system or the smart classroom management system. The number of students in the class indicates the total number of students participating in the course, which is usually obtained through the learning management system, the student information system, and the classroom access control and attendance system; the frequency of course opening, the class duration of each class, and the number of students in the class are stored as designated tags, and the designated tags are compared with the remote monitoring schemes of the smart classroom corresponding to the designated tags stored in the database to obtain the remote monitoring schemes of the smart classroom corresponding to the designated tags.

[0031] It needs to be explained that in the above-mentioned smart classroom, the combination of class frequency, class duration, and class size determines the configuration requirements of the monitoring system. High-frequency, large-class courses may require multi-angle and multi-device monitoring to ensure full coverage and data collection, while low-frequency, small-class courses may only require basic monitoring configuration, focusing on analysis of interaction and participation.

[0032] It should be explained that the above-mentioned comparison of key indicators such as class frequency, class duration, and class size can customize the most suitable monitoring plan for each class. Personalized plans can better adapt to the specific needs of different classes and improve the pertinence and effectiveness of monitoring effects. Different courses and classes of different sizes may have different monitoring needs. After comparing the specified tags, the system can automatically select the most suitable monitoring plan to cope with diverse classroom needs and provide more targeted support. By analyzing the basic information of the classroom, it can reasonably configure the resources of the monitoring system, such as cameras, microphones, bandwidth allocation, etc., to avoid waste or uneven distribution of resources. For large classrooms and high-frequency classes, the system can automatically allocate more resources to ensure monitoring quality.

[0033] It needs to be explained that the above remote monitoring plan for smart classrooms is obtained by analyzing and comparing the basic information of smart classrooms. Through the analysis of the basic information of smart classrooms, remote monitoring plans can be tailored according to specific needs. This customized plan can better adapt to different types of classrooms and teaching modes, ensuring the effectiveness and practicality of the monitoring system. Through comparative analysis, the specific needs of different classrooms can be accurately identified, and the monitoring plan can be optimized according to these needs. The monitoring plan can be more flexible and adapt to different classroom environments and changing teaching requirements. The monitoring strategy and collection frequency can be adjusted according to the data to ensure continuous optimization of the monitoring effect.

[0034] Based on the frequency of classroom teaching status collection, the classroom teaching status of the smart classroom remote monitoring communication link with qualified status is analyzed to determine whether the classroom teaching status is qualified.

[0035] Specifically, to determine whether the classroom teaching status is qualified, the specific analysis process is as follows: based on the classroom teaching status acquisition frequency, the classroom teaching status of the smart classroom remote monitoring communication link with a qualified status is analyzed to obtain a classroom teaching status data set, which specifically includes the teacher-student interaction frequency, student attendance rate, and teacher blackboard writing area; based on the obtained classroom teaching status data set, a comprehensive analysis is performed to obtain a classroom teaching status evaluation value, which is used as an analysis basis for determining whether the classroom teaching status is qualified; the classroom teaching status evaluation value is compared with the classroom teaching status reference evaluation value stored in the database; if the classroom teaching status evaluation value is higher than or equal to the classroom teaching status reference evaluation value, then the class is qualified. The classroom teaching status corresponding to the classroom teaching status evaluation value is qualified; if the classroom teaching status evaluation value is lower than the classroom teaching status reference evaluation value, the classroom teaching status corresponding to the classroom teaching status evaluation value is unqualified, and an alarm prompt is issued for the unqualified classroom teaching status, and a red warning window pops up on the teacher's computer screen. Through audio warnings, such as short beeps or voice reminders, the teacher is reminded that there is a problem. At the same time, the alarm information is sent to the academic affairs management department as part of the teaching quality monitoring for subsequent follow-up and improvement. Teachers can adjust the teaching methods according to the alarm information, such as speeding up or slowing down the teaching progress, increasing interactive links, or adjusting the difficulty of the teaching content to better attract students' attention.

[0036] It needs to be explained that the above-mentioned teacher-student interaction frequency measures the number of interactions between teachers and students, and is usually obtained through classroom management systems and audio / video analysis equipment. The student attendance rate measures the student attendance, and is usually obtained through electronic attendance systems, RFID / NFC devices, access control attendance systems, and online classroom tools. The teacher's blackboard area measures the area of ​​the blackboard or whiteboard used by teachers in class, and is usually obtained through smart blackboards / whiteboards, image analysis equipment, and handwriting board data collection. The interaction frequency can improve students' sense of participation and attendance rate. Appropriate use of blackboards can help convey information and support interaction. There needs to be a balance between the blackboard area and the interaction frequency to avoid monotony in the classroom. By monitoring these indicators, teachers and education administrators can promptly discover and solve problems in teaching and continuously improve the overall effectiveness of classroom teaching.

[0037] In a specific embodiment, key teaching indicators such as the frequency of interaction between teachers and students, student attendance, and the area of ​​teachers' blackboard writing are continuously monitored. The system can analyze the teaching status in the classroom. If the teaching status is found to be unsatisfactory, the system can immediately issue an alarm prompt, allowing teachers to adjust teaching strategies and improve teaching methods in a timely manner, thereby improving the overall teaching quality. The system's monitoring and alarm prompt functions help teachers to automatically manage the classroom and reduce the pressure of manual intervention, so that teachers can focus more on the teaching content itself, rather than spending energy on monitoring and management. By comparing the classroom teaching status evaluation value with the standard reference value, the system can ensure that each class meets the established teaching standards, maintain consistency in teaching quality, and avoid fluctuations in teaching quality due to individual differences. The monitoring and alarm system can cover every classroom in the school to ensure that all classrooms can meet the teaching standards. Through continuous feedback and adjustment, the system can promote continuous improvement and optimization of teaching.

[0038] Furthermore, the specific analysis process of classroom teaching status evaluation is as follows: ; In the formula, is the classroom teaching status evaluation value, The frequency of teacher-student interaction, For student attendance, The area for teachers to write on the blackboard. is the compensation factor for the set teacher-student interaction frequency, is the compensation factor for the set student attendance rate, It is the compensation factor for the set blackboard writing area of ​​the teacher.

[0039] It needs to be explained that the above-mentioned classroom teaching status evaluation value is calculated through the frequency of interaction between teachers and students, the attendance rate of students, and the area of ​​teachers' blackboard writing. The frequency of interaction between teachers and students, the attendance rate of students, and the area of ​​teachers' blackboard writing are normalized. The three indicators of the frequency of interaction between teachers and students, the attendance rate of students, and the area of ​​teachers' blackboard writing reflect multiple key aspects of classroom teaching from the perspectives of interaction, participation, and information transmission. Combining these indicators for evaluation can measure the effectiveness of classroom teaching more comprehensively, rather than just relying on a single dimension. Through the comprehensive evaluation of these objective indicators, the evaluation bias caused by the teacher's personal subjective judgment can be reduced, and a more objective and fair classroom teaching status measurement standard can be provided. The classroom teaching status evaluation value can provide feedback, allowing teachers to understand the current teaching status during the class and make timely adjustments. This timely feedback mechanism can help teachers dynamically adjust the teaching rhythm and content, thereby improving classroom management efficiency. , , It is the compensation factor corresponding to the teacher-student interaction frequency, student attendance rate, and teacher blackboard writing area preset in the database, which represents the numerical value of the influence of the teacher-student interaction frequency, student attendance rate, and teacher blackboard writing area on the classroom teaching status evaluation value. When used, the compensation factor corresponding to the teacher-student interaction frequency, student attendance rate, and teacher blackboard writing area can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the teacher-student interaction frequency, student attendance rate, and teacher blackboard writing area form a mapping set with the compensation factors of the teacher-student interaction frequency, student attendance rate, and teacher blackboard writing area preset in the database. The real-time teacher-student interaction frequency, student attendance rate, and teacher blackboard writing area are input into the mapping set to obtain the compensation factors corresponding to the teacher-student interaction frequency, student attendance rate, and teacher blackboard writing area. The mapping relationship can be one-to-one or many-to-one.

[0040] Based on the frequency of classroom audio status collection, the classroom audio status of the qualified smart classroom remote monitoring communication link is analyzed to determine whether the classroom audio status is qualified.

[0041] Specifically, to determine whether the classroom audio status is qualified, the specific analysis process is as follows: based on the classroom audio status acquisition frequency, analyze the classroom audio status of the smart classroom remote monitoring communication link with a qualified status, and obtain a classroom audio status data set. The classroom audio status data set specifically includes the absolute value of the difference between the teacher's speaking speed and the reference speaking speed, the classroom noise decibel value, and the proportion of the teacher's speaking time; based on the obtained classroom audio status data set, a comprehensive analysis is performed to obtain a classroom audio status evaluation value, and the classroom audio status evaluation value is used as an analysis basis for determining whether the classroom audio status is qualified; the classroom audio status evaluation value is compared with the classroom audio status reference evaluation value stored in the database; if the classroom audio status evaluation value is higher than or equal to the classroom audio status reference evaluation value, then the classroom audio status The classroom audio status corresponding to the evaluation value is qualified; if the classroom audio status evaluation value is lower than the classroom audio status reference evaluation value, the classroom audio status corresponding to the classroom audio status evaluation value is unqualified, and an alarm prompt is issued for the unqualified classroom audio status, and a short prompt sound (such as a slight beep or voice reminder) is inserted into the teacher's headphones or the classroom's audio equipment to remind the teacher that the current audio status is unqualified, such as the sound is too low, the background noise is too loud, or the audio equipment is faulty. The prompt sound should be designed to be short and not interfere with the normal progress of the class. Teachers can adjust the teaching method according to the type of audio problem. For example, if the volume is too low, the speaking volume can be appropriately increased or alternative equipment can be used. If the background noise is too loud, the teacher can temporarily suspend teaching and continue after the noise problem is resolved.

[0042] It should be explained that the absolute value of the difference between the above-mentioned teacher's speaking speed and the reference speaking speed measures the gap between the teacher's actual speaking speed and the standard speaking speed, which is usually obtained through voice analysis software, intelligent microphone system or classroom monitoring system. The classroom noise decibel value reflects the intensity of the noise in the classroom, which is usually obtained through noise measurement instrument, environmental monitoring system or intelligent classroom management system. The teacher's speaking time percentage indicates the proportion of the teacher's speaking time in the classroom, which is usually obtained through voice analysis software, intelligent microphone system or classroom monitoring system. The teacher's speaking speed directly affects the teacher's speaking time percentage. A faster speaking speed usually means that more information can be transmitted in a shorter time. Therefore, in the same amount of time, the teacher's speaking time percentage may decrease, while the time left for students to discuss, ask questions or other activities will increase. If the teacher speaks slowly, it may take up more class time, resulting in an increase in the teacher's speaking time percentage. The higher noise decibel value in the classroom may prompt the teacher to speed up the speaking speed in order to transmit information faster in a noisy environment, which may lead to an increase in the difference between the speaking speed and the reference speaking speed, affecting the teaching effect. In a noisy environment, teachers may need to pay more attention to the control of speaking speed to ensure that students can clearly understand the explanation.

[0043] In a specific embodiment, by monitoring and analyzing the audio status, feedback is provided to teachers to help them better manage classroom audio. The data-driven feedback mechanism enables teachers to adjust their speaking speed and tone in time during the teaching process, thereby improving teaching effectiveness. When the system detects that the noise level in the classroom is too high, it can issue an alarm to remind teachers to take measures to reduce interference and reduce noise. Teachers can focus more on teaching content, and students can learn in a quieter environment. By automatically monitoring the audio status and issuing alarm prompts when necessary, the system can reduce the burden of teachers' subjective judgment and adjustment of audio quality in class, improve the automation and intelligence level of classroom management, and continuously monitor and accumulate data. Schools can analyze long-term audio status data, identify common problems and take preventive measures, thereby continuously improving teaching quality.

[0044] Furthermore, the specific analysis process of the classroom audio status evaluation value is as follows: ; In the formula, is the classroom audio status evaluation value, is the absolute value of the difference between the teacher's speaking speed and the reference speaking speed, is the decibel value of classroom noise, The proportion of teachers' speaking time, is the compensation factor for the absolute value of the difference between the teacher's speaking speed and the reference speaking speed. is the compensation factor for the set classroom noise decibel value, is the compensation factor for the proportion of teacher’s speaking time, and e is a natural constant.

[0045] It should be explained that the above-mentioned classroom audio status evaluation value is calculated through the absolute value of the difference between the teacher's speaking speed and the reference speaking speed, the classroom noise decibel value, and the proportion of the teacher's speaking time. The absolute value of the difference between the teacher's speaking speed and the reference speaking speed, the classroom noise decibel value, and the proportion of the teacher's speaking time are normalized. The teacher's speaking speed, noise decibel value, and speaking time proportion reflect the overall quality of classroom audio from three key perspectives: voice clarity, environmental quietness, and teaching rhythm. Combining these indicators for evaluation can comprehensively measure the quality of classroom audio and ensure that the teaching content can be clearly and effectively conveyed to students. The evaluation value can provide teachers with audio status feedback to help teachers adjust the speaking speed, tone, and speaking time proportion according to actual conditions during the teaching process to optimize the classroom teaching effect. The system can automatically calculate and monitor the audio status evaluation value, and the system can automatically manage the classroom audio quality, reduce the burden of teachers' manual adjustment in class, and allow teachers to focus more on the teaching content itself. , , The absolute value of the difference between the teacher's speaking speed and the reference speaking speed, the classroom noise decibel value, and the compensation factor corresponding to the proportion of the teacher's speaking time preset in the database represent the numerical value of the influence of the absolute value of the difference between the teacher's speaking speed and the reference speaking speed, the classroom noise decibel value, and the proportion of the teacher's speaking time on the classroom audio status evaluation value. When used, the absolute value of the difference between the teacher's speaking speed and the reference speaking speed, the classroom noise decibel value, and the compensation factor corresponding to the proportion of the teacher's speaking time can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the absolute value of the difference between the teacher's speaking speed and the reference speaking speed, the classroom noise decibel value, the proportion of the teacher's speaking time, and the absolute value of the difference between the teacher's speaking speed and the reference speaking speed, the classroom noise decibel value, and the compensation factor of the teacher's speaking time preset in the database form a mapping set. The absolute value of the difference between the real-time teacher's speaking speed and the reference speaking speed, the classroom noise decibel value, and the proportion of the teacher's speaking time are input into the mapping set to obtain the absolute value of the difference between the teacher's speaking speed and the reference speaking speed, the classroom noise decibel value, and the compensation factor corresponding to the proportion of the teacher's speaking time. The mapping relationship can be one-to-one or many-to-one.

[0046] Based on the frequency of collecting students’ learning behavior status in the classroom, the learning behavior status of students in the classroom of the qualified smart classroom remote monitoring communication link is analyzed to determine whether the learning behavior status of students in the classroom is qualified.

[0047] Specifically, to determine whether the learning behavior status of classroom students is qualified, the specific analysis process is: based on the frequency of classroom student learning behavior status collection, the learning behavior status of classroom students in the smart classroom remote monitoring communication link with a qualified status is analyzed to obtain a classroom student learning behavior status data set; based on the obtained classroom student learning behavior status data set, a comprehensive analysis is performed to obtain a classroom student learning behavior status evaluation value, and the classroom student learning behavior status evaluation value is used as an analysis basis for determining whether the classroom student learning behavior status is qualified; the classroom student learning behavior status evaluation value is compared with the classroom student learning behavior status reference evaluation value stored in the database; if the classroom student learning behavior status evaluation value is higher than or equal to the classroom student learning behavior status reference evaluation value, then the classroom student learning behavior status is qualified. The learning behavior status of the classroom students corresponding to the status evaluation value is qualified; if the classroom student learning behavior status evaluation value is lower than the classroom student learning behavior status reference evaluation value, then the classroom student learning behavior status corresponding to the classroom student learning behavior status evaluation value is unqualified, and an alarm prompt is issued for the unqualified classroom student learning behavior status, and a short prompt sound is sent through the loudspeaker in the classroom or the teacher's headphones to remind the teacher that there is a student with unqualified learning behavior status. The volume should be designed not to interfere with the classroom to ensure the concealment and effectiveness of the reminder. After receiving the alarm prompt, the teacher can try to adjust the classroom management strategy, such as re-attracting students' attention through questions, interactive sessions, group discussions, etc., or reminding students to stay focused, and intervene in the unqualified classroom student learning behavior status.

[0048] It needs to be explained that the above-mentioned monitoring of students' learning behavior status, when an unqualified behavior status is found, the system will immediately issue an alarm prompt. The feedback mechanism allows teachers to take quick action, intervene or correct, so as to prevent students from continuing to maintain bad learning behaviors in class. Timely identification and correction of students' learning behavior problems can avoid the accumulation of these problems, thereby preventing them from affecting students' overall learning effects. Timely intervention can effectively reduce the long-term negative impact of bad learning behaviors. Through alarm prompts and status analysis, teachers can obtain specific learning behavior data to help teachers make more scientific teaching decisions. By timely identifying and intervening in unqualified learning behavior states, the system can help prevent students from having bigger problems in learning, such as falling behind or not understanding the course content, and help ensure that students always maintain good learning effects in class.

[0049] Furthermore, the dataset of students’ learning behavior status in the classroom specifically includes the frequency of students’ head movements, the frequency of students’ eye movements, and the angle between students’ sitting posture and the plumb plane.

[0050] It should be explained that the above-mentioned student head movement frequency measures the number of times the student's head moves, which is usually obtained through cameras and computer vision technology, infrared sensors, and gesture recognition systems. The student eye movement frequency measures the number of times the student's eyes move, which is usually obtained through eye trackers, cameras and eye tracking software, and virtual reality equipment. The angle between the student's sitting posture and the plumb plane measures the inclination angle of the student's sitting posture, which is usually obtained through gesture recognition systems, depth cameras, accelerometers, and gyroscopes. The student's head movement frequency and eye movement frequency can both be used as indicators of the student's attention. When students focus on a task (such as listening or reading), their head movement The frequency tends to be lower, while the eye movement frequency may be higher, especially when reading or observing a specific object. If a student moves his head frequently, this may indicate inattention or distraction in class. The eye movement frequency may also be irregular in this case. A more upright sitting posture (smaller angle from the plumb plane) is accompanied by less head movement. This is because when students sit upright, it is easier for them to focus on a fixed target (such as the blackboard or teacher) without moving their heads frequently. When students sit in an improper posture (such as leaning or leaning on the back of the chair), the frequency of head movements may increase, indicating that the student may be in a more relaxed or distracted state in class.

[0051] In a specific embodiment, the specific analysis process of the evaluation value of the learning behavior state of the classroom students is as follows: ; In the formula, Provide assessment values ​​for students’ learning behavior status in the classroom. is the frequency of students’ head movements, is the student's eye movement frequency, is the angle between the student's sitting position and the plumb plane, is the compensation factor for the set student head movement frequency, is the compensation factor for the set student eye movement frequency, The compensation factor for the angle between the student's sitting posture and the plumb plane.

[0052] It needs to be explained that the above-mentioned evaluation value of students' learning behavior status in class is calculated through the frequency of students' head movements, the frequency of students' eye movements, and the angle between students' sitting posture and the plumb plane. The frequency of students' head movements, the frequency of students' eye movements, and the angle between students' sitting posture and the plumb plane are normalized. The frequency of head movements, the frequency of eye movements, and the angle of sitting posture reflect students' attention, concentration, and participation from different angles respectively. The evaluation value calculated by combining these indicators can comprehensively reflect students' learning status in class and help teachers understand students' learning performance more accurately. The evaluation value can reflect students' learning status. If the evaluation value is low, the system can remind teachers in time, indicating that students' attention or participation may decline, and teachers can immediately take measures to make adjustments, such as adjusting the teaching rhythm, increasing interaction, or encouraging students to refocus. By automatically calculating and monitoring students' learning behavior status evaluation values ​​through the system, teachers can reduce the energy consumption of classroom management, rely on system feedback for management, and improve classroom management efficiency. , , The compensation factors corresponding to the student head movement frequency, student eye movement frequency, and the angle between the student sitting posture and the plumb plane preset in the database represent the numerical values ​​of the influence of the student head movement frequency, student eye movement frequency, and the angle between the student sitting posture and the plumb plane on the evaluation values ​​of the learning behavior status of the students in the classroom. When used, the compensation factors corresponding to the student head movement frequency, student eye movement frequency, and the angle between the student sitting posture and the plumb plane can be directly obtained from the database. The corresponding relationship can be a preset mapping relationship. For example, the student head movement frequency, student eye movement frequency, and the angle between the student sitting posture and the plumb plane are formed with the compensation factors of the student head movement frequency, student eye movement frequency, and the angle between the student sitting posture and the plumb plane preset in the database. The real-time student head movement frequency, student eye movement frequency, and the angle between the student sitting posture and the plumb plane are input into the mapping set to obtain the compensation factors corresponding to the student head movement frequency, student eye movement frequency, and the angle between the student sitting posture and the plumb plane. The mapping relationship can be one-to-one or many-to-one.

[0053] It needs to be explained that the above analysis of classroom teaching status, classroom audio status, and classroom student learning behavior status can comprehensively understand the classroom teaching effect from multiple angles. Teaching status analysis can reveal the delivery effect of teaching content, audio status analysis can ensure the clear communication of information, and learning behavior status analysis can evaluate students' participation and understanding. Multi-dimensional data analysis can help teachers and education managers discover specific problems in the classroom, such as too fast teaching pace, unclear audio, and students' lack of concentration, so as to make precise improvements and continuously optimize teaching methods, thereby improving the overall teaching quality.

[0054] Reference Figure 2 As shown, the second aspect of the present invention provides a smart classroom remote monitoring system, including a communication link status judgment module, a remote monitoring scheme comparison module, a classroom teaching status judgment module, a classroom audio status judgment module and a student learning behavior status judgment module.

[0055] The communication link status judgment module is used to analyze the status of the smart classroom remote monitoring communication link and determine whether the status of the smart classroom remote monitoring communication link is qualified.

[0056] The remote monitoring scheme comparison module is used to analyze the basic information of the smart classroom and obtain the remote monitoring scheme of the smart classroom by comparison. The remote monitoring scheme of the smart classroom specifically includes the frequency of collecting classroom teaching status, the frequency of collecting classroom audio status, and the frequency of collecting classroom student learning behavior status.

[0057] The classroom teaching status judgment module is used to analyze the classroom teaching status of the smart classroom remote monitoring communication link with qualified status based on the classroom teaching status collection frequency, and judge whether the classroom teaching status is qualified.

[0058] The classroom audio status judgment module is used to analyze the classroom audio status of the smart classroom remote monitoring communication link with qualified status based on the classroom audio status collection frequency, and judge whether the classroom audio status is qualified.

[0059] The student learning behavior status judgment module is used to analyze the learning behavior status of students in the smart classroom remote monitoring communication link with qualified status based on the frequency of classroom student learning behavior status collection, and judge whether the classroom student learning behavior status is qualified.

[0060] It needs to be explained that the above-mentioned remote monitoring method and system for a smart classroom can quickly judge the classroom teaching status, audio status and the eligibility of student learning behavior through data collection and analysis of appropriate frequency. This timely monitoring allows teachers to quickly understand the teaching progress in the classroom, discover and promptly correct possible problems, thereby improving the immediacy and effectiveness of classroom teaching. Multi-level monitoring and analysis can help education administrators obtain detailed classroom information, evaluate teachers' teaching performance and students' learning effects, and promote the improvement of overall teaching quality.

[0061] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A remote monitoring method for a smart classroom, characterized in that: The following steps are involved: Analyze the status of the remote monitoring communication link of the smart classroom to determine whether the status of the remote monitoring communication link of the smart classroom is qualified; Analyze the basic information of the smart classroom and compare it to obtain a smart classroom remote monitoring solution, which specifically includes the frequency of collecting classroom teaching status, the frequency of collecting classroom audio status, and the frequency of collecting classroom student learning behavior status; Based on the frequency of classroom teaching status collection, analyze the classroom teaching status of the qualified smart classroom remote monitoring communication link to determine whether the classroom teaching status is qualified; Based on the frequency of classroom audio status collection, analyze the classroom audio status of the qualified smart classroom remote monitoring communication link to determine whether the classroom audio status is qualified; Based on the frequency of collecting students’ learning behavior status in the classroom, the learning behavior status of students in the classroom of the qualified smart classroom remote monitoring communication link is analyzed to determine whether the learning behavior status of students in the classroom is qualified.

2. A smart classroom remote monitoring method according to claim 1, characterized in that: The specific analysis process of judging whether the status of the smart classroom remote monitoring communication link is qualified is as follows: Analyze the status of the remote monitoring communication link of the smart classroom and obtain the data set of the remote monitoring communication link status of the smart classroom. The remote monitoring communication link status of the smart classroom specifically includes the communication link transmission delay, the communication link network bandwidth, and the communication link packet loss rate; Based on the acquired smart classroom remote monitoring communication link status data set, a comprehensive analysis is performed to obtain a smart classroom remote monitoring communication link status evaluation value, which is used as an analysis basis for judging whether the smart classroom remote monitoring communication link status is qualified; Compare the smart classroom remote monitoring communication link state evaluation value with the smart classroom remote monitoring communication link state reference evaluation value stored in the database; If the smart classroom remote monitoring communication link state evaluation value is higher than or equal to the smart classroom remote monitoring communication link state reference evaluation value, then the smart classroom remote monitoring communication link state corresponding to the smart classroom remote monitoring communication link state evaluation value is qualified; If the smart classroom remote monitoring communication link status evaluation value is lower than the smart classroom remote monitoring communication link status reference evaluation value, the smart classroom remote monitoring communication link status corresponding to the smart classroom remote monitoring communication link status evaluation value is unqualified, and the unqualified smart classroom remote monitoring communication link is replaced.

3. According to claim 1, a smart classroom remote monitoring method is characterized by: The comparison results in a smart classroom remote monitoring solution, and the specific analysis process is as follows: Analyze the basic information of the smart classroom to obtain a data set of basic information of the smart classroom. The data set of basic information of the smart classroom specifically includes the frequency of classes, the duration of each class, and the number of students in the class; The frequency of classes, the duration of each class, and the number of students in the class are stored as designated tags, and the designated tags are compared with the smart classroom remote monitoring solutions corresponding to the designated tags stored in the database to obtain the smart classroom remote monitoring solutions corresponding to the designated tags.

4. According to claim 1, a remote monitoring method for a smart classroom is characterized by: The specific analysis process of judging whether the classroom teaching status is qualified is as follows: Based on the frequency of classroom teaching status collection, the classroom teaching status of the qualified smart classroom remote monitoring communication link is analyzed to obtain the classroom teaching status data set. The classroom teaching status data set specifically includes the frequency of teacher-student interaction, student attendance rate, and teacher blackboard area. Based on the acquired classroom teaching status data set, a comprehensive analysis is performed to obtain a classroom teaching status evaluation value, which is used as an analysis basis for judging whether the classroom teaching status is qualified; Compare the classroom teaching status evaluation value with the classroom teaching status reference evaluation value stored in the database; If the classroom teaching status evaluation value is higher than or equal to the classroom teaching status reference evaluation value, the classroom teaching status corresponding to the classroom teaching status evaluation value is qualified; If the classroom teaching status evaluation value is lower than the classroom teaching status reference evaluation value, the classroom teaching status corresponding to the classroom teaching status evaluation value is unqualified, and an alarm prompt is issued for the unqualified classroom teaching status.

5. A smart classroom remote monitoring method according to claim 4, characterized in that: The specific analysis process of the classroom teaching status evaluation value is as follows: ； In the formula, is the classroom teaching status evaluation value, The frequency of teacher-student interaction, For student attendance, The area for teachers to write on the blackboard. is the compensation factor for the set teacher-student interaction frequency, is the compensation factor for the set student attendance rate, It is the compensation factor for the set blackboard writing area of ​​the teacher.

6. A smart classroom remote monitoring method according to claim 1, characterized in that: The specific analysis process of judging whether the classroom audio status is qualified is as follows: Based on the frequency of classroom audio status collection, the classroom audio status of the qualified smart classroom remote monitoring communication link is analyzed to obtain the classroom audio status data set. The classroom audio status data set specifically includes the absolute value of the difference between the teacher's speaking speed and the reference speaking speed, the classroom noise decibel value, and the proportion of the teacher's speaking time; Based on the acquired classroom audio status data set, a classroom audio status evaluation value is obtained through comprehensive analysis, and the classroom audio status evaluation value is used as an analysis basis for judging whether the classroom audio status is qualified; Compare the classroom audio status evaluation value with the classroom audio status reference evaluation value stored in the database; If the classroom audio status evaluation value is higher than or equal to the classroom audio status reference evaluation value, the classroom audio status corresponding to the classroom audio status evaluation value is qualified; If the classroom audio status evaluation value is lower than the classroom audio status reference evaluation value, the classroom audio status corresponding to the classroom audio status evaluation value is unqualified, and an alarm prompt is issued for the unqualified classroom audio status.

7. A smart classroom remote monitoring method according to claim 6, characterized in that: The specific analysis process of the classroom audio status evaluation value is as follows: ； In the formula, is the classroom audio status evaluation value, is the absolute value of the difference between the teacher's speaking speed and the reference speaking speed, is the decibel value of classroom noise, The proportion of teachers' speaking time, is the compensation factor for the absolute value of the difference between the teacher's speaking speed and the reference speaking speed. is the compensation factor for the set classroom noise decibel value, is the compensation factor for the proportion of teacher’s speaking time, and e is a natural constant.

8. A smart classroom remote monitoring method according to claim 1, characterized in that: The specific analysis process of judging whether the learning behavior status of students in the classroom is qualified is as follows: Based on the frequency of collecting the learning behavior status of the students in the classroom, the learning behavior status of the students in the remote monitoring communication link of the smart classroom with qualified status is analyzed to obtain the learning behavior status data set of the students in the classroom. Based on the obtained learning behavior status data set of the students in the classroom, a comprehensive analysis is performed to obtain the evaluation value of the learning behavior status of the students in the classroom. The evaluation value of the learning behavior status of the students in the classroom is used as the analysis basis for judging whether the learning behavior status of the students in the classroom is qualified. Compare the classroom student learning behavior status evaluation value with the classroom student learning behavior status reference evaluation value stored in the database; If the evaluation value of the learning behavior status of the classroom students is higher than or equal to the reference evaluation value of the learning behavior status of the classroom students, then the learning behavior status of the classroom students corresponding to the evaluation value of the learning behavior status of the classroom students is qualified; If the classroom student learning behavior status evaluation value is lower than the classroom student learning behavior status reference evaluation value, the classroom student learning behavior status corresponding to the classroom student learning behavior status evaluation value is unqualified, and an alarm prompt is issued for the unqualified classroom student learning behavior status.

9. A smart classroom remote monitoring method according to claim 8, characterized in that: The classroom student learning behavior status data set specifically includes the student's head movement frequency, the student's eye movement frequency, and the angle between the student's sitting posture and the plumb plane.

10. A smart classroom remote monitoring system, using a smart classroom remote monitoring method as described in any one of claims 1 to 9, characterized in that: It includes a communication link status judgment module, a remote monitoring scheme comparison module, a classroom teaching status judgment module, a classroom audio status judgment module and a student learning behavior status judgment module, among which: The communication link status judgment module is used to analyze the status of the smart classroom remote monitoring communication link and judge whether the status of the smart classroom remote monitoring communication link is qualified; The remote monitoring scheme comparison module is used to analyze the basic information of the smart classroom and compare to obtain the remote monitoring scheme of the smart classroom. The remote monitoring scheme of the smart classroom specifically includes the frequency of collecting classroom teaching status, the frequency of collecting classroom audio status, and the frequency of collecting classroom student learning behavior status; The classroom teaching status judgment module is used to analyze the classroom teaching status of the smart classroom remote monitoring communication link with a qualified status based on the classroom teaching status collection frequency, and judge whether the classroom teaching status is qualified; The classroom audio status judgment module is used to analyze the classroom audio status of the smart classroom remote monitoring communication link with a qualified status based on the classroom audio status acquisition frequency, and judge whether the classroom audio status is qualified; The student learning behavior status judgment module is used to analyze the learning behavior status of students in the smart classroom remote monitoring communication link classroom with qualified status based on the frequency of classroom student learning behavior status collection, and judge whether the classroom student learning behavior status is qualified.

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