Student mental health intelligent monitoring system and method driven by campus interaction data

Abstract

The invention relates to the technical field of information and communication of health data, and particularly discloses an intelligent student mental health monitoring system and method driven by campus interaction data. According to the system, a psychological health evaluation data set collection module, a data receiving performance perfection judgment module, a data feedback duration factor processing module and an evaluation efficiency index analysis module are arranged, a campus intelligent monitoring cloud platform receives student interaction data, and psychological health is evaluated through a psychological evaluation subsystem; acquiring data receiving performance of teacher and parent terminals, evaluating and comparing with a threshold value, forming teacher and parent response terminals after the performance is perfected, receiving a psychological health evaluation data set by the two terminals, calculating a feedback duration factor, combining data receiving performance evaluation values of the response terminals, analyzing an evaluation efficiency index, and evaluating the psychological health evaluation data set by the two terminals. And finally, the interactive data evaluation of the campus intelligent monitoring cloud platform is fed back, so that teachers and parents can master the mental health evaluation results of the students in time, and the utilization rate of the campus intelligent monitoring cloud platform is improved.

Description

Technical Field

[0001] The present invention relates to the field of information and communication technology of health data, and in particular to a student mental health intelligent monitoring system and method driven by campus interactive data. Background Art

[0002] In recent years, campus informatization construction has made significant progress, providing schools with more convenient and efficient means of information management. By building a campus informatization platform, real-time collection, storage and analysis of student data can be realized, providing strong technical support for intelligent monitoring of mental health. In addition, campus informatization can also promote communication between home and school, interaction between teachers and students, etc., providing more comprehensive protection for students' mental health.

[0003] For example, the invention patent with publication number CN109949935A announces a personalized terminal service campus health platform based on artificial intelligence, especially an artificial intelligence-based campus health management platform, which is characterized by obtaining the health information of each individual, and establishing health models in three aspects: mental health, physical health, and physical health. According to the above health model, information records based on time are added to establish an artificial intelligence dynamic data model, which is divided into three models: mental health, physical health, and physical health. The three separate dynamic data artificial intelligences are connected to the artificial intelligence campus health platform for big data analysis, labeling, evaluation, and statistics. Multi-dimensional data analysis, modeling, output, and linking are performed based on platform management. The health application data dynamically generated by the platform is output to two terminals, one is the dynamic health management data provided to managers, and the other is the health management data provided to students, teachers, and parents. It will be used for health management of individuals and managers through the terminal APP.

[0004] Combining the above technical solutions, it is found that there is a campus platform health monitoring technical solution. The analysis of information transmission between the platform and the terminal is relatively simple, which may lead to a decrease in the work efficiency of the campus platform and affect the health management of students. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a campus interactive data-driven intelligent student mental health monitoring system and method, 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: The first aspect of the present invention provides a student mental health intelligent monitoring system driven by campus interactive data, including: a mental health assessment data set collection module, which is used for the campus intelligent monitoring cloud platform to respond to and receive students' interactive data, and evaluate the students' interactive data through the psychological assessment subsystem belonging to the campus intelligent monitoring cloud platform to obtain the students' mental health assessment data set; a data reception performance improvement judgment module, which is used to obtain the data reception performance information of the teacher terminal and the data reception performance information of the parent terminal, respectively determine the data reception performance evaluation value of the teacher terminal and the data reception performance evaluation value of the parent terminal, and compare them with the data reception performance threshold value respectively to obtain performance comparison results, and determine whether to improve the data reception performance of the teacher terminal and the data reception performance of the parent terminal based on the performance comparison results. The data are improved and finally recorded as the teacher response terminal and the parent response terminal respectively; the data feedback duration factor processing module is used for the teacher response terminal and the parent response terminal to receive the student's mental health assessment data set sent by the campus intelligent monitoring cloud platform, thereby obtaining the mental health assessment feedback duration of the teacher response terminal and the mental health assessment feedback duration of the parent response terminal, and obtaining the data feedback duration factor of the teacher response terminal and the data feedback duration factor of the parent response terminal through data processing; the evaluation efficiency index analysis module is used to analyze the evaluation efficiency index of the campus intelligent monitoring cloud platform according to the data feedback duration factor of the teacher response terminal and the data feedback duration factor of the parent response terminal, the data reception performance evaluation value of the teacher response terminal and the data reception performance evaluation value of the parent response terminal, and finally provide feedback on the interactive data evaluation of the campus intelligent monitoring cloud platform.

[0007] As a further solution, the data reception performance evaluation value of the teacher terminal and the data reception performance evaluation value of the parent terminal are determined, and the specific analysis process is: obtaining the communication transmission network data between the teacher terminal and the campus intelligent monitoring cloud platform and the communication transmission network data between the parent terminal and the campus intelligent monitoring cloud platform, and obtaining the communication transmission network influence coefficient corresponding to the teacher terminal and the communication transmission network influence coefficient corresponding to the parent terminal after data processing respectively; extracting the data reception reference response time and the data reception reference rate from the monitoring cloud platform information library; based on the data reception performance information of the teacher terminal and the communication transmission network influence coefficient corresponding to the teacher terminal, a comprehensive analysis is performed to obtain the data reception performance evaluation value of the teacher terminal, and based on the data reception performance information of the parent terminal and the communication transmission network influence coefficient corresponding to the parent terminal, a comprehensive analysis is performed to obtain the data reception performance evaluation value of the parent terminal.

[0008] As a further solution, the performance comparison results are specifically a first performance comparison result and a second performance comparison result; the first performance comparison result is that the data reception performance evaluation value of the teacher terminal and the data reception performance evaluation value of the parent terminal are both greater than or equal to the data reception performance threshold; the second performance comparison result is that the data reception performance evaluation value of the teacher terminal is less than the data reception performance threshold or the data reception performance evaluation value of the parent terminal is less than the data reception performance threshold.

[0009] As a further solution, the data feedback duration factor of the teacher response terminal and the data feedback duration factor of the parent response terminal are obtained through data processing. The specific analysis process is: obtaining the receiving time point of the teacher response terminal receiving the mental health assessment data set and the receiving time point of the parent response terminal receiving the mental health assessment data set; obtaining the feedback time point of the teacher response terminal feeding back to the campus intelligent monitoring cloud platform and the feedback time point of the parent response terminal feeding back to the campus intelligent monitoring cloud platform; the mental health assessment feedback duration of the teacher response terminal, specifically the feedback time point of the teacher response terminal feeding back to the campus intelligent monitoring cloud platform and the time point when the teacher response terminal receives the mental health assessment data the difference between the receiving time points of the teacher response terminal and the receiving time points of the parent response terminal; the psychological health assessment feedback duration of the parent response terminal, specifically the difference between the feedback time point when the parent response terminal feeds back to the campus intelligent monitoring cloud platform and the receiving time point when the parent response terminal receives the psychological health assessment data set; the psychological health assessment feedback definition duration is extracted from the monitoring cloud platform information database; according to the psychological health assessment feedback duration of the teacher response terminal, the psychological health assessment feedback duration of the parent response terminal, the communication transmission network influence coefficient corresponding to the teacher terminal and the communication transmission network influence coefficient corresponding to the parent terminal, the data feedback duration factor of the teacher response terminal and the data feedback duration factor of the parent response terminal are obtained by data processing respectively.

[0010] As a further solution, the evaluation efficiency index of the campus intelligent monitoring cloud platform is analyzed, and the specific analysis process is: obtaining the evaluation efficiency information of the campus intelligent monitoring cloud platform, specifically including the video stream processing speed and evaluation response time of the campus intelligent monitoring cloud platform during the evaluation period; obtaining the data reception performance evaluation value of the teacher response terminal and the data reception performance evaluation value of the parent response terminal; the data reception performance evaluation value of the teacher response terminal and the data reception performance evaluation value of the parent response terminal are respectively obtained according to the data reception performance evaluation value of the teacher terminal, the data reception performance evaluation value of the parent terminal, and the improved teacher terminal is recorded as the teacher response terminal, and the improved parent terminal is recorded as the parent response terminal; according to the evaluation efficiency information of the campus intelligent monitoring cloud platform, the data feedback time factor of the teacher response terminal, the data feedback time factor of the parent response terminal, the data reception performance evaluation value of the teacher response terminal and the data reception performance evaluation value of the parent response terminal, the evaluation efficiency index of the campus intelligent monitoring cloud platform is analyzed, and the specific method is as follows:

[0011] In the formula, It is the evaluation efficiency index of the campus intelligent monitoring cloud platform. It is the evaluation response time of the campus intelligent monitoring cloud platform during the evaluation cycle. is the data feedback duration factor of the teacher response terminal, The data feedback duration factor of the parent response terminal, The video stream processing speed of the campus intelligent monitoring cloud platform during the evaluation period. is the data receiving performance evaluation value of the teacher response terminal, is the data receiving performance evaluation value of the parent response terminal, It is the weight factor corresponding to the video stream processing speed predefined in the monitoring cloud platform information library. is the weight factor corresponding to the data reception performance evaluation value of the teacher response terminal predefined in the monitoring cloud platform information database, is the weight factor corresponding to the data reception performance evaluation value of the parent response terminal predefined in the monitoring cloud platform information library, and e is a natural constant.

[0012] As a further solution, the interactive data evaluation of the campus intelligent monitoring cloud platform is fed back. The specific feedback process is: the evaluation efficiency index of the campus intelligent monitoring cloud platform is verified with the predefined evaluation efficiency index preset value to generate a data evaluation assessment label. If the evaluation efficiency index of the campus intelligent monitoring cloud platform is greater than the evaluation efficiency index preset value, the data evaluation assessment label is defined as a data evaluation assessment qualified label; if the evaluation efficiency index of the campus intelligent monitoring cloud platform is less than or equal to the evaluation efficiency index preset value, the data evaluation assessment label is defined as a data evaluation assessment abnormal label, so as to issue an early warning for the interactive data evaluation of the campus intelligent monitoring cloud platform.

[0013] The second aspect of the present invention provides a method for intelligent monitoring of student mental health driven by campus interactive data, including: collection of mental health assessment data sets: the campus intelligent monitoring cloud platform responds to and receives the interactive data of students, and evaluates the interactive data of students through the psychological assessment subsystem of the campus intelligent monitoring cloud platform to obtain the mental health assessment data set of students; data reception performance improvement judgment: obtaining the data reception performance information of the teacher terminal and the data reception performance information of the parent terminal, respectively determining the data reception performance evaluation value of the teacher terminal and the data reception performance evaluation value of the parent terminal, and comparing them with the data reception performance threshold value respectively to obtain performance comparison results, and determining whether to improve the data reception performance of the teacher terminal and the data reception performance of the parent terminal based on the performance comparison results, and finally recording them as the teacher terminal and the parent terminal respectively. Response terminal and parent response terminal; data feedback time factor processing: the teacher response terminal and the parent response terminal receive the students' mental health assessment data set sent by the campus intelligent monitoring cloud platform, thereby obtaining the mental health assessment feedback time of the teacher response terminal and the mental health assessment feedback time of the parent response terminal, and obtaining the data feedback time factor of the teacher response terminal and the data feedback time factor of the parent response terminal through data processing; evaluation efficiency index analysis: according to the data feedback time factor of the teacher response terminal and the data feedback time factor of the parent response terminal, the data reception performance evaluation value of the teacher response terminal and the data reception performance evaluation value of the parent response terminal are comprehensively considered to analyze the evaluation efficiency index of the campus intelligent monitoring cloud platform, and finally feedback is given to the interactive data evaluation of the campus intelligent monitoring cloud platform.

[0014] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0015] (1) The present invention provides a student mental health intelligent monitoring system and method driven by campus interactive data. The campus intelligent monitoring cloud platform receives student interactive data and can understand students' learning status, emotional changes and behavioral habits in real time. The psychological evaluation subsystem evaluates mental health, obtains the data receiving performance of teachers and parents' terminals, evaluates and compares it with the threshold, and forms teacher and parent response terminals after improving the performance, which can ensure accurate and timely transmission of information and improve communication efficiency. The two terminals receive the mental health evaluation data set and calculate the feedback duration factor, which can evaluate the response speed of the campus intelligent monitoring cloud platform when receiving data between the terminals. Combined with the data receiving performance evaluation value of the response terminal, the evaluation efficiency index is analyzed. Finally, the interactive data evaluation of the campus intelligent monitoring cloud platform is fed back, which can enable teachers and parents to grasp the students' mental health evaluation results in a timely manner and improve the utilization rate of the campus intelligent monitoring cloud platform.

[0016] (2) The present invention can ensure the efficiency and accuracy of the student's evaluation information during the transmission process by determining the data reception performance evaluation value of the teacher's terminal and the data reception performance evaluation value of the parent's terminal, and determining whether to improve the data reception performance of the teacher's terminal and the data reception performance of the parent's terminal. This reduces the possibility of information transmission delay or loss due to poor terminal performance, and terminals with improved performance help protect the student's evaluation information and prevent data leakage and abuse.

[0017] (3) The present invention analyzes the evaluation efficiency indicators of the campus intelligent monitoring cloud platform to reveal the performance of the cloud platform in terms of data transmission, storage, etc., so that the platform can quickly respond to abnormal situations and reduce the platform's false positives and false negatives of student information, thereby improving the accuracy and efficiency of student monitoring and ensuring the security of student information and the reliability of the platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] 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.

[0019] Figure 1 It is a schematic diagram of system module connection of the present invention.

[0020] Figure 2 The figure is a schematic flow chart of the method steps of the present invention. DETAILED DESCRIPTION

[0021] 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.

[0022] Reference Figure 1 As shown, the first aspect of the present invention provides a campus interactive data-driven student mental health intelligent monitoring system, including: a mental health assessment data set collection module, a data receiving performance improvement judgment module, a data feedback time factor processing module, and an assessment efficiency index analysis module.

[0023] The first aspect of the present invention provides a campus interactive data-driven student mental health intelligent monitoring system, which also includes: a monitoring cloud platform information library for storing data reception reference response time, data reception reference rate, mental health assessment feedback definition time, and preset values ​​of various factors, etc.

[0024] The mental health assessment data set collection module and the data reception performance improvement judgment module are both connected to the data feedback duration factor processing module, the data feedback duration factor processing module is connected to the assessment efficiency index analysis module, and the data reception performance improvement judgment module and the assessment efficiency index analysis module are both connected to the monitoring cloud platform information database.

[0025] The mental health assessment data set collection module is used for the campus intelligent monitoring cloud platform to respond to and receive students' interactive data, and to evaluate the students' interactive data through the psychological assessment subsystem of the campus intelligent monitoring cloud platform to obtain the students' mental health assessment data set.

[0026] The above-mentioned campus intelligent monitoring cloud platform is a comprehensive security management system that integrates advanced information technology and intelligent analysis functions. By integrating and integrating information technology of schools under the jurisdiction of the education department, a campus security intelligent monitoring service platform is formed that integrates intelligent video surveillance, video intelligent analysis, intelligent capture of student emotions and other security service functions. When the system detects that the student's mental state is abnormal, it automatically issues an early warning to notify teachers and parents.

[0027] The above-mentioned students' interactive data are collected in real time through various electronic devices and platforms used by students at school, such as basic information platforms, campus consumption platforms, campus safety platforms, campus interactive platforms, academic affairs management systems, etc. The data categories include but are not limited to texts, such as messages, mood records, anonymous confessions, help posts, leave instructions, voice, such as parent-child messages, videos, such as parent-child messages, etc.

[0028] The above-mentioned psychological assessment subsystem refers to a tool system specifically used to quantify and evaluate students' psychological characteristics. The psychological assessment subsystem evaluates students' interaction data to obtain students' mental health assessment data sets. Specifically, it uses students' interaction data received by the campus intelligent monitoring cloud platform as input, and uses natural language processing technology to analyze students' text and voice data to identify emotional states, such as joy, sadness, anxiety, etc.; analyzes students' behavioral data through machine learning algorithms to identify potential mental health risk patterns; analyzes students' social interaction data to understand their social status and interpersonal relationships as a reference for psychological state assessment; combines students' personal background, historical data and newly collected data to conduct personalized psychological state assessments, and outputs students' mental health assessment results; when a student's mental state is detected to be abnormal, the system automatically issues an early warning to notify educators and parents.

[0029] The above-mentioned students' mental health assessment data set may include students' basic information, such as name, student number, age, etc., students' psychological characteristic data, such as emotional state, psychological state, etc., students' physiological characteristic data, such as heart rate, facial expression, etc. These data constitute the students' psychological assessment results, which are displayed through the campus intelligent monitoring cloud platform connected to the psychological assessment subsystem, and ultimately achieve the measurement of students' mental health level.

[0030] The students' mental health assessment dataset may include but is not limited to data in the picture dimension, such as micro-expressions and students' emotional state, data in the sound dimension, such as laughing, crying, begging, sighing, etc., and data in the text dimension, such as message interactions, tree hole information, mood records, etc.

[0031] The data reception performance improvement determination module is used to obtain the data reception performance information of the teacher terminal and the data reception performance information of the parent terminal, determine the data reception performance evaluation value of the teacher terminal and the data reception performance evaluation value of the parent terminal respectively, and compare them with the data reception performance threshold value respectively to obtain a performance comparison result, and determine whether to improve the data reception performance of the teacher terminal and the data reception performance of the parent terminal based on the performance comparison result, and finally record them as the teacher response terminal and the parent response terminal respectively.

[0032] Specifically, the data reception performance information of the teacher terminal includes the data reception response duration, data reception rate, and the number of times the teacher terminal receives garbled data within the performance evaluation period.

[0033] The data reception performance information of the parent terminal specifically includes the data reception response duration, data reception rate, and number of times the parent terminal receives garbled data within a performance evaluation period.

[0034] The data receiving performance information of the teacher terminal and the data receiving performance information of the parent terminal can be extracted from the operation reports of the teacher terminal and the parent terminal.

[0035] The above-mentioned performance evaluation cycle is specifically a period of time used to evaluate the data reception performance status of the teacher terminal and the parent terminal. The performance evaluation cycle is determined by the platform manager based on analysis of factors such as the terminal status, platform usage status, and actual needs.

[0036] Furthermore, the data reception performance evaluation value of the teacher terminal and the data reception performance evaluation value of the parent terminal are determined by the specific analysis process as follows:

[0037] The communication transmission network data between the teacher terminal and the campus intelligent monitoring cloud platform and the communication transmission network data between the parent terminal and the campus intelligent monitoring cloud platform are obtained, and the communication transmission network influence coefficient corresponding to the teacher terminal and the communication transmission network influence coefficient corresponding to the parent terminal are obtained after data processing.

[0038] The communication transmission network data between the above-mentioned teacher terminal and the campus intelligent monitoring cloud platform specifically includes the maximum network delay duration between the teacher terminal and the cloud platform during the performance evaluation period, the network packet loss rate between the teacher terminal and the cloud platform at each performance evaluation time point, the network bandwidth between the teacher terminal and the cloud platform during the performance evaluation period, and the channel utilization rate between the teacher terminal and the cloud platform at each performance evaluation time point. Among them, the network delay duration, network packet loss rate, network bandwidth and channel utilization rate can all be extracted from the background operation log after the campus intelligent monitoring cloud platform establishes communication with the teacher terminal.

[0039] The above-mentioned performance evaluation time points are specifically a number of performance evaluation time points obtained by dividing the performance evaluation cycle into time points.

[0040] The communication transmission network data between the above-mentioned parent terminal and the campus intelligent monitoring cloud platform specifically includes the maximum network delay duration between the parent terminal and the cloud platform during the performance evaluation period, the network packet loss rate between the parent terminal and the cloud platform at each performance evaluation time point, the network bandwidth between the parent terminal and the cloud platform during the performance evaluation period, and the channel utilization rate between the parent terminal and the cloud platform at each performance evaluation time point. Among them, the network delay duration, network packet loss rate, network bandwidth and channel utilization rate can all be extracted from the background operation log after the campus intelligent monitoring cloud platform establishes communication with the parent terminal.

[0041] Based on the communication transmission network data between the teacher terminal and the campus intelligent monitoring cloud platform, a comprehensive analysis is performed to obtain the communication transmission network impact coefficient corresponding to the teacher terminal. At the same time, based on the communication transmission network data between the parent terminal and the campus intelligent monitoring cloud platform, a comprehensive analysis is performed to obtain the communication transmission network impact coefficient corresponding to the parent terminal.

[0042] In this embodiment, the analysis process of the communication transmission network influence coefficient corresponding to the teacher terminal is taken as an example, and the communication transmission network influence coefficient corresponding to the parent terminal is not repeated. The specific analysis method of the communication transmission network influence coefficient corresponding to the teacher terminal is as follows:

[0043] In the formula, is the communication transmission network impact coefficient corresponding to the teacher terminal, which is used in this embodiment to measure the influence of the network quality on the data transmission quality during the communication transmission between the teacher terminal and the campus intelligent monitoring cloud platform.

[0044] It is the maximum duration of network delay between teacher terminal and cloud platform during the performance evaluation cycle. max represents the maximum value, which refers to the maximum time required for data to be transmitted from one end of the network, i.e., teacher terminal, to the other end, i.e., campus intelligent monitoring cloud platform, during the performance evaluation cycle.

[0045] is the network packet loss rate between the teacher terminal and the cloud platform at the yth performance evaluation time point, which refers to the ratio of the number of data packets lost during data transmission between the teacher terminal and the cloud platform at each performance evaluation time point to the total number of data packets transmitted.

[0046] y is the number of each performance evaluation time point, , Y is the total number of performance evaluation time points.

[0047] is the channel utilization rate between the teacher terminal and the cloud platform at the yth performance evaluation time point, which refers to the proportion of time that the data transmission channel between the teacher terminal and the cloud platform is occupied by effective data transmission at each performance evaluation time point.

[0048] The channel utilization reference value predefined for monitoring the cloud platform information database refers to the set standard value of the channel utilization.

[0049] The network bandwidth between the teacher terminal and the cloud platform during the performance evaluation period refers to the ability of the channel in the network between the teacher terminal and the cloud platform to transmit data, that is, the "maximum data rate" that the channel in the network can pass in unit time.

[0050] The impact factor corresponding to the maximum unit value of network delay duration predefined in the monitoring cloud platform information database.

[0051] In a specific embodiment, the impact factor corresponding to the unit value of the maximum network delay duration can be directly obtained from the monitoring cloud platform information library when in use. The factor represents the numerical value of the degree of influence on the communication transmission network impact coefficient corresponding to the teacher terminal during the communication transmission network impact assessment corresponding to the teacher terminal. The corresponding relationship can be a pre-set mapping relationship. For example, the maximum network delay duration and the impact factor corresponding to the unit value of the maximum network delay duration preset in the monitoring cloud platform information library form a mapping set, and the real-time maximum network delay duration is brought into the mapping set to obtain the impact factor corresponding to the unit value of the maximum network delay duration. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, its value range is (0, 1).

[0052] The impact factor corresponding to the unit value of the network packet loss rate predefined in the monitoring cloud platform information database.

[0053] In a specific embodiment, the impact factor corresponding to the unit value of the network packet loss rate can be directly obtained from the monitoring cloud platform information library when in use. The factor represents the numerical value of the degree of influence on the communication transmission network impact coefficient corresponding to the teacher terminal during the communication transmission network impact assessment corresponding to the teacher terminal. The corresponding relationship can be a pre-set mapping relationship. For example, the network packet loss rate and the impact factor corresponding to the unit value of the network packet loss rate preset in the monitoring cloud platform information library form a mapping set, and the real-time network packet loss rate is brought into the mapping set to obtain the impact factor corresponding to the unit value of the network packet loss rate. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, its value range is (0, 1).

[0054] The impact factor corresponding to the network bandwidth unit value predefined in the monitoring cloud platform information database.

[0055] In a specific embodiment, the impact factor corresponding to the unit value of the network bandwidth can be directly obtained from the monitoring cloud platform information library when in use. The factor represents the numerical value of the degree of influence on the communication transmission network impact coefficient corresponding to the teacher terminal during the communication transmission network impact assessment corresponding to the teacher terminal. The corresponding relationship can be a pre-set mapping relationship. For example, the network bandwidth and the impact factor corresponding to the unit value of the network bandwidth preset in the monitoring cloud platform information library form a mapping set, and the real-time network bandwidth is brought into the mapping set to obtain the impact factor corresponding to the unit value of the network bandwidth. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, its value range is (0, 1).

[0056] In this embodiment, the network delay time is inversely proportional to the network bandwidth. Under the same traffic volume, that is, the amount of data, the larger the channel, that is, the bandwidth, the less likely the network is to be congested, and the shorter the network delay time is. An increase in bandwidth can usually reduce the packet loss rate, because when the bandwidth is large enough, the network can process a large amount of data more effectively and reduce the packet loss caused by network congestion. When the network is congested, it may take longer for the data packet to reach the receiving end, resulting in an increase in the network delay time. At the same time, due to network congestion or insufficient device processing capacity, some data packets may be discarded, resulting in an increase in the packet loss rate. In addition, retransmission may be required after packet loss, which will further increase the network delay time. The level of channel utilization directly affects the network delay time and packet loss rate. When the channel utilization is too high, the network congestion is aggravated, and the network delay time and packet loss rate will increase. If the channel utilization is too low, it may indicate that network resources are not fully utilized. Therefore, the channel utilization needs to be relatively close to or equal to the channel utilization reference value, so as to keep the network transmission quality in the best state and reduce the communication transmission network impact coefficient corresponding to the teacher terminal.

[0057] The data reception reference response time and data reception reference rate are extracted from the monitoring cloud platform information database.

[0058] According to the data reception performance information of the teacher terminal and the communication transmission network influence coefficient corresponding to the teacher terminal, a comprehensive analysis is performed to obtain the data reception performance evaluation value of the teacher terminal, and according to the data reception performance information of the parent terminal and the communication transmission network influence coefficient corresponding to the parent terminal, a comprehensive analysis is performed to obtain the data reception performance evaluation value of the parent terminal. The specific method is as follows:

[0059] In the formula, is the data reception performance evaluation value of the teacher's terminal. In this embodiment, it is a quantitative value obtained after evaluating the performance of the terminal device used by the teacher in receiving data. The higher the data reception performance evaluation value of the teacher's terminal, the better the performance of the terminal in terms of data reception speed, stability and accuracy, and can better meet the needs of establishing data transmission between the teacher's terminal and the campus intelligent monitoring cloud platform.

[0060] The data reception response time of the teacher terminal during the performance evaluation period refers to the length of time from the teacher terminal receiving the data transmission request sent by the campus intelligent monitoring cloud platform to the teacher terminal successfully receiving the data, reflecting the performance and efficiency of the terminal in receiving data.

[0061] The reference response time for data reception refers to a predefined standard value of the response time for data reception.

[0062] The data receiving rate of the teacher's terminal during the performance evaluation period refers to the average speed at which the terminal device used by the teacher receives data during the performance evaluation period. This rate reflects how fast the terminal receives data.

[0063] The data receiving reference rate refers to a predefined standard value of the data receiving rate.

[0064] It needs to be explained that the comparison between the data reception response time of the teacher terminal during the performance evaluation period and the data reception reference response time, as well as the comparison between the data reception rate of the teacher terminal during the performance evaluation period and the data reception reference rate, reduces the excessive load on the teacher terminal that may be caused when the data reception response time or the data reception rate is too fast, thereby affecting its stability and performance, and if the teacher terminal cannot effectively process a large amount of data in a short time, it may cause an increase in the data processing error rate; at the same time, it reduces the possibility of long waiting time or incomplete data reception during the data reception process caused by the data reception response time or the data reception rate being too slow.

[0065] The number of times the teacher terminal receives garbled data during the performance evaluation period refers to the number of times the terminal device used by the teacher receives data that cannot be correctly identified or displayed, that is, garbled data, during the performance evaluation period.

[0066] is the communication transmission network impact coefficient corresponding to the teacher terminal, which means that the communication transmission network impact coefficient corresponding to the teacher terminal is obtained through comprehensive analysis of the maximum network delay between the teacher terminal and the cloud platform during the performance evaluation period, the network packet loss rate between the teacher terminal and the cloud platform at each performance evaluation time point, the network bandwidth between the teacher terminal and the cloud platform during the performance evaluation period, and the channel utilization rate between the teacher terminal and the cloud platform at each performance evaluation time point.

[0067] It is the impact factor corresponding to the teacher terminal receiving garbled data once, which is predefined in the monitoring cloud platform information database.

[0068] In a specific embodiment, the impact factor corresponding to a single reception of garbled data by a teacher terminal can be directly obtained from the monitoring cloud platform information library when in use. The factor represents the numerical value of the degree of influence on the data reception performance evaluation value of the teacher terminal during the data reception performance evaluation of the teacher terminal. The corresponding relationship can be a pre-set mapping relationship. For example, the number of times the teacher terminal receives garbled data and the impact factor corresponding to a single reception of garbled data by the teacher terminal preset in the monitoring cloud platform information library form a mapping set. The real-time number of times the teacher terminal receives garbled data is brought into the mapping set to obtain the impact factor corresponding to a single reception of garbled data by the teacher terminal. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, its value range is (0, 1).

[0069] is the data reception performance evaluation value of the parent terminal. In this embodiment, it is a quantitative value obtained after evaluating the performance of the terminal device used by the parent in receiving data. The higher the data reception performance evaluation value of the parent terminal, the better the performance of the terminal in terms of data reception speed, stability and accuracy, and can better meet the needs of establishing data transmission between the parent terminal and the campus intelligent monitoring cloud platform.

[0070] The data reception response time of the parent terminal within the performance evaluation period refers to the length of time from the time the parent terminal receives the data transmission request sent by the campus intelligent monitoring cloud platform to the time the parent terminal successfully receives the data.

[0071] The data receiving rate of the parent terminal during the performance evaluation period refers to the average speed at which the terminal device used by the parent receives data during the performance evaluation period.

[0072] The number of times the parent terminal receives garbled data during the performance evaluation period refers to the number of times the terminal device used by the parent receives data that cannot be correctly identified or displayed, that is, garbled data, during the performance evaluation period.

[0073] is the communication transmission network impact coefficient corresponding to the parent terminal, which means that the communication transmission network impact coefficient corresponding to the parent terminal is obtained through comprehensive analysis of the maximum network delay between the parent terminal and the cloud platform during the performance evaluation period, the network packet loss rate between the parent terminal and the cloud platform at each performance evaluation time point, the network bandwidth between the parent terminal and the cloud platform during the performance evaluation period, and the channel utilization rate between the parent terminal and the cloud platform at each performance evaluation time point.

[0074] It is the impact factor corresponding to a single reception of garbled data by a parent terminal predefined in the monitoring cloud platform information database.

[0075] In a specific embodiment, the impact factor corresponding to a single reception of garbled data by a parent terminal can be directly obtained from the monitoring cloud platform information library when in use. The factor represents a numerical value of the degree of influence on the data reception performance evaluation value of the parent terminal during the data reception performance evaluation of the parent terminal. The corresponding relationship can be a pre-set mapping relationship. For example, the number of times the parent terminal receives garbled data and the impact factor corresponding to a single reception of garbled data by the parent terminal preset in the monitoring cloud platform information library form a mapping set. The real-time number of times the parent terminal receives garbled data is brought into the mapping set to obtain the impact factor corresponding to a single reception of garbled data by the parent terminal. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, its value range is (0, 1).

[0076] js and jz represent the teacher terminal and parent terminal respectively.

[0077] It should be explained that the effects expressed by the above-mentioned teacher terminal and parent terminal are consistent effects, so the corresponding effect of the teacher terminal is taken as an example in this embodiment, and the parent terminal will not be described in detail.

[0078] In this embodiment, the data reception response time and the data reception rate jointly affect the data processing efficiency of the teacher terminal. When the data reception response time and the data reception rate are closer to the corresponding reference values, the teacher terminal can obtain and process data faster, thereby improving the data transmission efficiency between the teacher terminal and the campus intelligent monitoring cloud platform; the number of times garbled data is received reflects the data reception quality of the teacher terminal. A lower number of garbled data reception times indicates that the teacher terminal can stably and accurately receive data, thereby ensuring the integrity and accuracy of the transmitted information; if the data reception response time and the data reception rate are farther away from the corresponding reference values, it may cause the waiting time in the data reception process to be too long or the data reception to be incomplete, thereby increasing the possibility of receiving garbled data; conversely, if the data reception response speed of the teacher terminal is fast, the time is short and the reception rate is high, and they are all close to the corresponding reference values, but the number of times garbled data is received is still large, it means that the teacher terminal may have problems such as decoding errors or hardware failures, which need to be further investigated and resolved.

[0079] In this embodiment, network bandwidth is the cornerstone of the data receiving performance of the teacher terminal. A higher network bandwidth means a greater data transmission capacity, thereby being able to support a higher data reception rate. In the data reception process of the teacher terminal, the shorter the delay time, the better the real-time performance of the data transmission. In the performance evaluation, if the packet loss rate of the communication transmission network is high, then the data reception performance evaluation value of the teacher terminal will also be reduced accordingly. Therefore, increasing the network bandwidth, reducing the delay time and the packet loss rate, thereby reducing the communication transmission network influence coefficient corresponding to the teacher terminal, thereby reducing the negative impact of its coefficient on the performance evaluation of the teacher terminal.

[0080] Specifically, the obtained performance comparison results are specifically a first performance comparison result and a second performance comparison result;

[0081] The first performance comparison result is that the data reception performance evaluation value of the teacher terminal and the data reception performance evaluation value of the parent terminal are both greater than or equal to the data reception performance threshold value predefined in the monitoring cloud platform information library.

[0082] The second performance comparison result is that the data reception performance evaluation value of the teacher terminal is less than the data reception performance threshold or the data reception performance evaluation value of the parent terminal is less than the data reception performance threshold.

[0083] The above-mentioned second performance comparison result specifically includes that the data reception performance evaluation value of the teacher terminal is less than the data reception performance threshold and the data reception performance evaluation value of the parent terminal is greater than or equal to the data reception performance threshold, the data reception performance evaluation value of the teacher terminal is greater than or equal to the data reception performance threshold and the data reception performance evaluation value of the parent terminal is less than the data reception performance threshold, and the data reception performance evaluation value of the teacher terminal is less than the data reception performance threshold and the data reception performance evaluation value of the parent terminal is less than the data reception performance threshold.

[0084] Further, the determination of whether to improve the data receiving performance of the teacher terminal and the data receiving performance of the parent terminal based on the performance comparison result is specifically carried out as follows:

[0085] If the performance comparison result shows the first performance comparison result, there is no need to improve the data reception performance of the teacher terminal and the data reception performance of the parent terminal, and the teacher terminal is directly recorded as the teacher response terminal and the parent terminal is directly recorded as the parent response terminal.

[0086] If the performance comparison result is displayed as the second performance comparison result, and the data reception performance evaluation value of the teacher terminal is displayed as less than the data reception performance threshold, the data reception performance of the teacher terminal is improved; if the performance comparison result is displayed as the second performance comparison result, and the data reception performance evaluation value of the parent terminal is displayed as less than the data reception performance threshold, the data reception performance of the parent terminal is improved, and the improved teacher terminal is recorded as the teacher response terminal, and the improved parent terminal is recorded as the parent response terminal.

[0087] The above-mentioned improvement of data receiving performance specifically utilizes the advantages of multi-core processors to simultaneously process multiple data receiving tasks through parallel processing and multi-threading technology, thereby increasing the data receiving rate of the terminal; using an asynchronous processing mechanism to separate data receiving and processing tasks, thereby increasing the response speed and reducing the data receiving response time; adding check codes or error correction codes during data transmission to enable data to be checked and corrected at the receiving end, thereby reducing the number of times garbled data is received; real-time monitoring of network performance, timely detection and resolution of network failures or congestion problems, and reduction of network packet loss rates; and load balancing technology to distribute traffic to multiple servers or network devices to avoid single-point overload and improve channel utilization.

[0088] Through the above operations, the terminal can receive data faster and improve the real-time and efficiency of data processing; when the terminal receives data, the delay and packet loss rate will be significantly reduced, ensuring the integrity and accuracy of the data; the terminal's network connection will be more stable, reducing the occurrence of network interruptions and failures; the terminal can more effectively utilize channel resources, improve data transmission efficiency and bandwidth utilization. In summary, the operation of improving the terminal data reception performance can effectively improve its performance, so that the improved terminal performance meets the needs of data reception.

[0089] The data feedback duration factor processing module is used for the teacher response terminal and the parent response terminal to receive the student's mental health assessment data set sent by the campus intelligent monitoring cloud platform, thereby obtaining the mental health assessment feedback duration of the teacher response terminal and the mental health assessment feedback duration of the parent response terminal, and obtaining the data feedback duration factor of the teacher response terminal and the data feedback duration factor of the parent response terminal through data processing.

[0090] Specifically, the data feedback duration factor of the teacher response terminal and the data feedback duration factor of the parent response terminal are obtained through data processing, and the specific analysis process is as follows:

[0091] Obtain the time point at which the teacher response terminal receives the mental health assessment data set and the time point at which the parent response terminal receives the mental health assessment data set.

[0092] The above-mentioned receiving time point can be extracted from the data receiving report of the teacher response terminal and the parent response terminal.

[0093] Obtain the time point at which the teacher's response terminal feeds back the campus intelligent monitoring cloud platform, and the time point at which the parent's response terminal feeds back the campus intelligent monitoring cloud platform.

[0094] The above feedback time points can be extracted from the data feedback report of the campus intelligent monitoring cloud platform.

[0095] The psychological health assessment feedback duration of the teacher response terminal is specifically the difference between the feedback time point when the teacher response terminal feeds back to the campus intelligent monitoring cloud platform and the reception time point when the teacher response terminal receives the psychological health assessment data set.

[0096] In a specific embodiment, if the time point at which the teacher response terminal receives the mental health assessment data set is 13:00, and the time point at which the teacher response terminal provides feedback to the campus intelligent monitoring cloud platform is 13:10, then the mental health assessment feedback duration of the teacher response terminal is 10 minutes, and the difference between 13:10 and 13:00, that is, the mental health assessment feedback duration of the teacher response terminal is 10 minutes.

[0097] The psychological health assessment feedback duration of the parent response terminal is specifically the difference between the feedback time point when the parent response terminal feeds back to the campus intelligent monitoring cloud platform and the reception time point when the parent response terminal receives the psychological health assessment data set.

[0098] The defined duration of mental health assessment feedback is extracted from the monitoring cloud platform information database.

[0099] According to the psychological health assessment feedback time of the teacher response terminal, the psychological health assessment feedback time of the parent response terminal, the communication transmission network influence coefficient corresponding to the teacher terminal, and the communication transmission network influence coefficient corresponding to the parent terminal, the data feedback time factor of the teacher response terminal and the data feedback time factor of the parent response terminal are obtained by data processing respectively. The specific method is as follows:

[0100] In the formula, It is the data feedback time factor of the teacher response terminal, which is used in this embodiment to measure the influence degree corresponding to the length of time from when the teacher terminal receives the student evaluation information from the platform to when it gives feedback.

[0101] It is the data feedback time factor of the parent response terminal, which is used in this embodiment to measure the influence degree corresponding to the length of time from when the parent terminal receives the student evaluation information from the platform to when it gives feedback.

[0102] The feedback time point from the teacher's response terminal to the campus intelligent monitoring cloud platform refers to the specific time when the teacher sends feedback information to the campus intelligent monitoring cloud platform through the response terminal after receiving the student evaluation information.

[0103] The receiving time point of the mental health assessment data set received by the teacher response terminal refers to the specific time when the teacher receives the student assessment information through the response terminal.

[0104] The feedback time point that the parent response terminal feeds back to the campus intelligent monitoring cloud platform refers to the specific time when the parent sends feedback information to the campus intelligent monitoring cloud platform through the response terminal after receiving the student evaluation information.

[0105] The receiving time point of the mental health assessment data set received by the parent response terminal refers to the specific time when the parent receives the student assessment information through the response terminal.

[0106] Defining the duration for mental health assessment feedback refers to the maximum value of the predefined mental health assessment feedback duration.

[0107] is the communication transmission network influence coefficient corresponding to the teacher terminal, is the communication transmission network influence coefficient corresponding to the parent terminal, Represented as reception and feedback respectively.

[0108] In this embodiment, when the difference between the data feedback time point and the receiving time point is smaller and much smaller than the defined time length of the psychological health assessment feedback, it means that the data feedback speed is faster, and the campus intelligent monitoring cloud platform and the teacher terminal and the parent terminal can establish a good connection and communication, and each other can obtain the required information more timely. The smaller difference also helps to reduce data loss and errors during transmission, because the probability of network failure or interference in a shorter time window is relatively low; in summary, the smaller the difference between the data feedback time point and the receiving time point, the faster the data feedback speed, and the negative impact of the feedback time length will be smaller, thereby improving the evaluation efficiency of the campus intelligent monitoring cloud platform.

[0109] In the process of establishing connection and communication between the campus intelligent monitoring cloud platform and the teacher terminal and the parent terminal, the communication transmission network influence coefficient corresponding to the teacher terminal and the parent terminal will also have a negative impact on the communication between the platform and the terminal. In the process of data reception and feedback, the communication transmission network influence coefficient will directly affect the data transmission speed and accuracy. When the network conditions are poor, such as high network delay and high packet loss rate, the data transmission speed will slow down and the feedback time will be extended accordingly, which will cause the data feedback time factor to increase and reduce the response speed between the platform and the terminal. Therefore, necessary measures need to be taken to effectively reduce the data feedback time factor and improve the overall performance of the platform evaluation.

[0110] The evaluation efficiency index analysis module is used to analyze the evaluation efficiency index of the campus intelligent monitoring cloud platform according to the data feedback duration factor of the teacher response terminal and the data feedback duration factor of the parent response terminal, and comprehensively consider the data reception performance evaluation value of the teacher response terminal and the data reception performance evaluation value of the parent response terminal, and finally provide feedback on the interactive data evaluation of the campus intelligent monitoring cloud platform.

[0111] Furthermore, the evaluation efficiency index of the campus intelligent monitoring cloud platform is analyzed, and the specific analysis process is as follows:

[0112] Obtain information on the evaluation efficiency of the campus intelligent monitoring cloud platform, including the video stream processing speed and evaluation response time of the campus intelligent monitoring cloud platform during the evaluation period.

[0113] The information on the evaluation efficiency of the campus intelligent monitoring cloud platform can be extracted from the operation report of the background operation system of the campus intelligent monitoring cloud platform.

[0114] The above-mentioned evaluation cycle specifically refers to the total time required for the campus intelligent monitoring cloud platform to receive data, evaluate data, feedback results and store data. The evaluation cycle is determined by the platform management personnel based on a comprehensive analysis of factors such as the operating status of the campus intelligent monitoring cloud platform, actual evaluation needs, and specific student information.

[0115] The data reception performance evaluation value of the teacher response terminal and the data reception performance evaluation value of the parent response terminal are obtained.

[0116] The data reception performance evaluation value of the teacher response terminal and the data reception performance evaluation value of the parent response terminal are respectively obtained based on the data reception performance evaluation value of the teacher terminal, the data reception performance evaluation value of the parent terminal, and the improved teacher terminal is recorded as the teacher response terminal, and the improved parent terminal is recorded as the parent response terminal.

[0117] According to the evaluation efficiency information of the campus intelligent monitoring cloud platform, the data feedback time factor of the teacher response terminal, the data feedback time factor of the parent response terminal, the data reception performance evaluation value of the teacher response terminal and the data reception performance evaluation value of the parent response terminal, the evaluation efficiency index of the campus intelligent monitoring cloud platform is analyzed. The specific method is as follows:

[0118] In the formula, It is an evaluation efficiency index of the campus intelligent monitoring cloud platform. In this embodiment, it is a series of indicators used to measure the speed and efficiency of the campus intelligent monitoring cloud platform in processing monitoring tasks, responding to requests, data transmission, etc.

[0119] The evaluation response time of the campus intelligent monitoring cloud platform during the evaluation cycle refers to the total time required for the campus intelligent monitoring cloud platform to receive the evaluation instruction and start executing the evaluation task during the evaluation cycle.

[0120] is the data feedback duration factor of the teacher response terminal, which means that the data feedback duration factor of the teacher terminal is obtained by comprehensive analysis of the psychological health assessment feedback duration of the teacher response terminal and the communication transmission network influence coefficient corresponding to the teacher terminal.

[0121] is the data feedback duration factor of the parent response terminal, which means that the data feedback duration factor of the parent terminal is obtained by comprehensive analysis of the psychological health assessment feedback duration of the parent response terminal and the communication transmission network influence coefficient corresponding to the parent terminal.

[0122] It is the video stream processing speed of the campus intelligent monitoring cloud platform during the evaluation period, which refers to the efficiency of the campus intelligent monitoring cloud platform in processing video data during the evaluation period.

[0123] The data reception performance evaluation value of the teacher response terminal refers to the data reception performance evaluation value of the teacher terminal after the data reception performance improvement operation.

[0124] The data reception performance evaluation value of the parent response terminal refers to the data reception performance evaluation value of the parent terminal after the data reception performance improvement operation.

[0125] It is the weight factor corresponding to the video stream processing speed predefined in the monitoring cloud platform information library.

[0126] In a specific embodiment, the weight factor corresponding to the video stream processing speed can be directly obtained from the monitoring cloud platform information library when in use. The factor represents the numerical value of the degree of influence on the evaluation efficiency index of the campus intelligent monitoring cloud platform during the evaluation efficiency evaluation of the campus intelligent monitoring cloud platform. The corresponding relationship can be a pre-set mapping relationship. For example, the video stream processing speed and the weight factor corresponding to the preset video stream processing speed in the monitoring cloud platform information library form a mapping set, and the real-time video stream processing speed is brought into the mapping set to obtain the weight factor corresponding to the video stream processing speed. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, its value range is (0, 1).

[0127] It is the weight factor corresponding to the data reception performance evaluation value of the teacher response terminal predefined in the monitoring cloud platform information library.

[0128] In a specific embodiment, the weight factor corresponding to the data reception performance evaluation value of the teacher response terminal can be directly obtained from the monitoring cloud platform information library when in use. The factor represents the numerical value of the degree of influence on the evaluation efficiency index of the campus intelligent monitoring cloud platform during the evaluation efficiency evaluation of the campus intelligent monitoring cloud platform. The corresponding relationship can be a pre-set mapping relationship. For example, the data reception performance evaluation value of the teacher response terminal and the weight factor corresponding to the data reception performance evaluation value of the teacher response terminal preset in the monitoring cloud platform information library form a mapping set, and the real-time data reception performance evaluation value of the teacher response terminal is brought into the mapping set to obtain the weight factor corresponding to the data reception performance evaluation value of the teacher response terminal. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, its value range is (0, 1).

[0129] is the weight factor corresponding to the data reception performance evaluation value of the parent response terminal predefined in the monitoring cloud platform information library, and e is a natural constant.

[0130] In a specific embodiment, the weight factor corresponding to the data reception performance evaluation value of the parent response terminal can be directly obtained from the monitoring cloud platform information library when in use. The factor represents the numerical value of the degree of influence on the evaluation efficiency index of the campus intelligent monitoring cloud platform during the evaluation efficiency evaluation of the campus intelligent monitoring cloud platform. The corresponding relationship can be a pre-set mapping relationship. For example, the data reception performance evaluation value of the parent response terminal and the weight factor corresponding to the data reception performance evaluation value of the parent response terminal preset in the monitoring cloud platform information library form a mapping set, and the real-time data reception performance evaluation value of the parent response terminal is brought into the mapping set to obtain the weight factor corresponding to the data reception performance evaluation value of the parent response terminal. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, its value range is (0, 1).

[0131] In this embodiment, the data feedback time factor of the teacher terminal and the parent terminal, the video stream processing speed and the evaluation response time together constitute the chain of information feedback of the campus intelligent monitoring cloud platform. If the feedback time of any link is too long, it will affect the efficiency and effect of the information feedback of the entire cloud platform. The data feedback time of the teacher terminal is affected by the evaluation response time. If the evaluation subsystem responds slowly, the feedback time for the teacher to obtain student data will be correspondingly extended. Similarly, the data feedback time of the parent terminal is also affected by the evaluation subsystem, and the increase in the video stream processing speed will reduce the evaluation response time. In order to improve the efficiency of cloud platform information feedback, necessary measures need to be taken to improve the response speed of the evaluation subsystem and the video stream processing speed, such as using performance monitoring tools to monitor subsystem performance indicators in real time, timely discover the performance bottleneck of the subsystem, improve the response speed of the evaluation subsystem, use multi-threading, multi-process and other parallel processing methods, process multiple video streams at the same time, and improve the overall processing speed, thereby shortening the evaluation response time. At the same time, it is also necessary to improve the data processing capabilities of the teacher terminal and the parent terminal, shorten the data feedback time factor, and jointly increase the evaluation efficiency index of the campus intelligent monitoring cloud platform.

[0132] In this embodiment, the data processing performance of the teacher and parent response terminals jointly affects the system stability of the campus intelligent monitoring cloud platform. If the terminal performance is poor, it may cause the cloud platform to freeze or crash when transmitting large amounts of data, affecting the evaluation efficiency. The data processing performance of the terminal also directly affects the quality of the evaluation results. If the terminal performance is good, the cloud platform can transmit the evaluation results to the terminal more completely and accurately, and can also obtain the feedback results of the terminal faster. Therefore, ensuring that the terminal has good data processing performance can improve the evaluation efficiency of the campus intelligent monitoring cloud platform to better support the data processing needs of the evaluation.

[0133] Specifically, the feedback of the interactive data evaluation of the campus intelligent monitoring cloud platform is as follows:

[0134] The evaluation efficiency index of the campus intelligent monitoring cloud platform is verified with the preset value of the evaluation efficiency index predefined in the monitoring cloud platform information library to generate a data evaluation label. If the evaluation efficiency index of the campus intelligent monitoring cloud platform is greater than the preset value of the evaluation efficiency index, the data evaluation label is defined as a data evaluation qualified label.

[0135] If the evaluation efficiency index of the campus intelligent monitoring cloud platform is less than or equal to the preset value of the evaluation efficiency index, the data evaluation assessment label is defined as a data evaluation assessment abnormal label, so as to issue an early warning for the interactive data evaluation of the campus intelligent monitoring cloud platform.

[0136] Furthermore, the interactive data evaluation of the campus intelligent monitoring cloud platform is warned, specifically, the evaluation efficiency between the campus intelligent monitoring cloud platform and the teacher response terminal is warned, and the evaluation efficiency between the campus intelligent monitoring cloud platform and the parent response terminal is warned at the same time.

[0137] The above-mentioned warning, specifically, is that if the warning mechanism identifies the generation of abnormal labels for data evaluation, the warning mechanism will be triggered, and warning information will be sent to platform managers via SMS, phone calls, emails, etc. Based on the warning information, platform managers can quickly take emergency measures to solve problems in the evaluation process of the campus intelligent monitoring cloud platform. For example, the evaluation response time of the campus intelligent monitoring cloud platform is greatly increased due to excessive load during the evaluation process. During the evaluation process, other unnecessary programs or services can be closed to reduce the platform load and shorten the evaluation response time. Alternatively, cluster technology can be used to combine multiple servers into a whole to jointly process evaluation tasks to shorten the evaluation response time.

[0138] The above-mentioned early warning mechanism refers to a system that conducts real-time monitoring and early warning of the information transmission and feedback performance between the campus intelligent monitoring cloud platform and the teacher terminals and parent terminals. This mechanism aims to promptly discover and solve problems in the evaluation process of the campus intelligent monitoring cloud platform, ensure the accurate and timely transmission of information, and improve the efficiency and security of the use of the campus intelligent monitoring cloud platform.

[0139] It should be explained that the campus intelligent monitoring cloud platform involved in the present invention forms a continuous and efficient process from receiving to analyzing and then transmitting the students' interactive data, aiming to achieve continuous monitoring of students' mental health. The platform can receive data from students' online learning, social interaction and other aspects in real time to identify changes in students' mental state. At the same time, the platform will transmit the analysis results to teachers and parents' terminals in a timely manner so that they can take intervention measures in time. This process not only improves the timeliness of monitoring students' mental health, but also effectively expands teachers' and parents' comprehensive understanding and grasp of students' mental state.

[0140] Reference Figure 2 As shown, the second aspect of the present invention provides a method for intelligently monitoring student mental health driven by campus interactive data, comprising:

[0141] Collection of mental health assessment data sets: The campus intelligent monitoring cloud platform responds to and receives students’ interaction data, and evaluates the students’ interaction data through the psychological assessment subsystem of the campus intelligent monitoring cloud platform to obtain the students’ mental health assessment data sets.

[0142] Data reception performance improvement judgment: obtain the data reception performance information of the teacher terminal and the data reception performance information of the parent terminal, determine the data reception performance evaluation value of the teacher terminal and the data reception performance evaluation value of the parent terminal respectively, and compare them with the data reception performance threshold respectively to obtain the performance comparison result, and determine whether to improve the data reception performance of the teacher terminal and the data reception performance of the parent terminal based on the performance comparison result, and finally record them as the teacher response terminal and the parent response terminal respectively.

[0143] Data feedback duration factor processing: The teacher response terminal and the parent response terminal receive the students' mental health assessment data set sent by the campus intelligent monitoring cloud platform, thereby obtaining the mental health assessment feedback duration of the teacher response terminal and the mental health assessment feedback duration of the parent response terminal, and the data feedback duration factor of the teacher response terminal and the parent response terminal are obtained through data processing.

[0144] Evaluation efficiency index analysis: According to the data feedback time factor of the teacher response terminal and the data feedback time factor of the parent response terminal, the data reception performance evaluation value of the teacher response terminal and the data reception performance evaluation value of the parent response terminal are comprehensively analyzed to analyze the evaluation efficiency index of the campus intelligent monitoring cloud platform, and finally feedback is given to the interactive data evaluation of the campus intelligent monitoring cloud platform.

[0145] 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 present invention, they should all fall within the protection scope of the present invention.

Claims

1. The intelligent monitoring system for students' mental health driven by campus interactive data is characterized by: include: The mental health assessment data set collection module is used for the campus intelligent monitoring cloud platform to respond to and receive the students' interactive data, and to evaluate the students' interactive data through the psychological assessment subsystem of the campus intelligent monitoring cloud platform to obtain the students' mental health assessment data set; A data reception performance improvement determination module is used to obtain data reception performance information of the teacher terminal and data reception performance information of the parent terminal, determine the data reception performance evaluation value of the teacher terminal and the data reception performance evaluation value of the parent terminal respectively, and compare them with the data reception performance threshold respectively to obtain a performance comparison result, and determine whether to improve the data reception performance of the teacher terminal and the data reception performance of the parent terminal based on the performance comparison result, and finally record them as the teacher response terminal and the parent response terminal respectively; The data feedback duration factor processing module is used for the teacher response terminal and the parent response terminal to receive the student's mental health assessment data set sent by the campus intelligent monitoring cloud platform, thereby obtaining the mental health assessment feedback duration of the teacher response terminal and the mental health assessment feedback duration of the parent response terminal, and obtaining the data feedback duration factor of the teacher response terminal and the data feedback duration factor of the parent response terminal through data processing; The evaluation efficiency index analysis module is used to analyze the evaluation efficiency index of the campus intelligent monitoring cloud platform according to the data feedback time factor of the teacher response terminal and the data feedback time factor of the parent response terminal, the data reception performance evaluation value of the teacher response terminal and the data reception performance evaluation value of the parent response terminal, and finally provide feedback on the interactive data evaluation of the campus intelligent monitoring cloud platform.

2. The campus interactive data-driven student mental health intelligent monitoring system according to claim 1 is characterized by: The data reception performance information of the teacher terminal specifically includes the data reception response time, data reception rate, and number of times the teacher terminal receives garbled data during the performance evaluation period; The data reception performance information of the parent terminal specifically includes the data reception response duration, data reception rate, and number of times the parent terminal receives garbled data within a performance evaluation period.

3. The campus interactive data-driven student mental health intelligent monitoring system according to claim 1 is characterized by: The specific analysis process of determining the data reception performance evaluation value of the teacher terminal and the data reception performance evaluation value of the parent terminal is as follows: Acquire the communication transmission network data between the teacher terminal and the campus intelligent monitoring cloud platform and the communication transmission network data between the parent terminal and the campus intelligent monitoring cloud platform, and obtain the communication transmission network influence coefficient corresponding to the teacher terminal and the communication transmission network influence coefficient corresponding to the parent terminal after performing data processing respectively; Extract the data receiving reference response time and data receiving reference rate from the monitoring cloud platform information database; Based on the data reception performance information of the teacher terminal and the communication transmission network influence coefficient corresponding to the teacher terminal, a comprehensive analysis is performed to obtain the data reception performance evaluation value of the teacher terminal, and based on the data reception performance information of the parent terminal and the communication transmission network influence coefficient corresponding to the parent terminal, a comprehensive analysis is performed to obtain the data reception performance evaluation value of the parent terminal.

4. The campus interactive data-driven student mental health intelligent monitoring system according to claim 1 is characterized by: The obtained performance comparison results are specifically a first performance comparison result and a second performance comparison result; The first performance comparison result is that the data reception performance evaluation value of the teacher terminal and the data reception performance evaluation value of the parent terminal are both greater than or equal to the data reception performance threshold; The second performance comparison result is that the data reception performance evaluation value of the teacher terminal is less than the data reception performance threshold or the data reception performance evaluation value of the parent terminal is less than the data reception performance threshold.

5. The campus interactive data-driven student mental health intelligent monitoring system according to claim 4 is characterized by: The specific determination process of determining whether to improve the data receiving performance of the teacher terminal and the data receiving performance of the parent terminal based on the performance comparison result is as follows: If the performance comparison result is the first performance comparison result, there is no need to improve the data receiving performance of the teacher terminal and the data receiving performance of the parent terminal, and the teacher terminal is directly recorded as the teacher response terminal, and the parent terminal is directly recorded as the parent response terminal; If the performance comparison result is displayed as the second performance comparison result, and the data reception performance evaluation value of the teacher terminal is displayed as less than the data reception performance threshold, the data reception performance of the teacher terminal is improved; if the performance comparison result is displayed as the second performance comparison result, and the data reception performance evaluation value of the parent terminal is displayed as less than the data reception performance threshold, the data reception performance of the parent terminal is improved, and the improved teacher terminal is recorded as the teacher response terminal, and the improved parent terminal is recorded as the parent response terminal.

6. The campus interactive data-driven student mental health intelligent monitoring system according to claim 1 is characterized by: The data feedback duration factor of the teacher response terminal and the data feedback duration factor of the parent response terminal are obtained through data processing. The specific analysis process is as follows: Obtaining the time point at which the teacher response terminal receives the mental health assessment data set and the time point at which the parent response terminal receives the mental health assessment data set; Obtain the time point at which the teacher's response terminal feeds back the campus intelligent monitoring cloud platform, and the time point at which the parent's response terminal feeds back the campus intelligent monitoring cloud platform; The psychological health assessment feedback duration of the teacher response terminal is specifically the difference between the feedback time point when the teacher response terminal feeds back to the campus intelligent monitoring cloud platform and the reception time point when the teacher response terminal receives the psychological health assessment data set; The psychological health assessment feedback duration of the parent response terminal is specifically the difference between the feedback time point when the parent response terminal feeds back to the campus intelligent monitoring cloud platform and the reception time point when the parent response terminal receives the psychological health assessment data set; Extract the defined duration of mental health assessment feedback from the monitoring cloud platform information database; According to the psychological health assessment feedback time of the teacher response terminal, the psychological health assessment feedback time of the parent response terminal, the communication transmission network influence coefficient corresponding to the teacher terminal and the communication transmission network influence coefficient corresponding to the parent terminal, data processing is performed to obtain the data feedback time factor of the teacher response terminal and the data feedback time factor of the parent response terminal.

7. The campus interactive data-driven student mental health intelligent monitoring system according to claim 1 is characterized by: The analysis of the evaluation efficiency indicators of the campus intelligent monitoring cloud platform is as follows: Obtain information on the evaluation efficiency of the campus intelligent monitoring cloud platform, including the video stream processing speed and evaluation response time of the campus intelligent monitoring cloud platform during the evaluation period; Obtaining a data receiving performance evaluation value of a teacher response terminal and a data receiving performance evaluation value of a parent response terminal; The data reception performance evaluation value of the teacher response terminal and the data reception performance evaluation value of the parent response terminal are obtained based on the data reception performance evaluation value of the teacher terminal, the data reception performance evaluation value of the parent terminal, and the improved teacher terminal is recorded as the teacher response terminal and the improved parent terminal is recorded as the parent response terminal. According to the evaluation efficiency information of the campus intelligent monitoring cloud platform, the data feedback time factor of the teacher response terminal, the data feedback time factor of the parent response terminal, the data reception performance evaluation value of the teacher response terminal and the data reception performance evaluation value of the parent response terminal, the evaluation efficiency index of the campus intelligent monitoring cloud platform is analyzed. The specific method is as follows: In the formula, It is the evaluation efficiency index of the campus intelligent monitoring cloud platform. It is the evaluation response time of the campus intelligent monitoring cloud platform during the evaluation cycle. is the data feedback duration factor of the teacher response terminal, The data feedback duration factor of the parent response terminal, The video stream processing speed of the campus intelligent monitoring cloud platform during the evaluation period. is the data receiving performance evaluation value of the teacher response terminal, is the data receiving performance evaluation value of the parent response terminal, It is the weight factor corresponding to the video stream processing speed predefined in the monitoring cloud platform information library. is the weight factor corresponding to the data reception performance evaluation value of the teacher response terminal predefined in the monitoring cloud platform information database, is the weight factor corresponding to the data reception performance evaluation value of the parent response terminal predefined in the monitoring cloud platform information library, and e is a natural constant.

8. The campus interactive data-driven student mental health intelligent monitoring system according to claim 1 is characterized by: The feedback of the interactive data evaluation of the campus intelligent monitoring cloud platform is as follows: Verify the evaluation efficiency index of the campus intelligent monitoring cloud platform with the predefined evaluation efficiency index preset value to generate a data evaluation label. If the evaluation efficiency index of the campus intelligent monitoring cloud platform is greater than the evaluation efficiency index preset value, define the data evaluation label as a data evaluation qualified label. If the evaluation efficiency index of the campus intelligent monitoring cloud platform is less than or equal to the preset value of the evaluation efficiency index, the data evaluation assessment label is defined as a data evaluation assessment abnormal label, so as to issue an early warning for the interactive data evaluation of the campus intelligent monitoring cloud platform.

9. The campus interactive data-driven student mental health intelligent monitoring system according to claim 8 is characterized by: The above-mentioned early warning of the interactive data evaluation of the campus intelligent monitoring cloud platform is specifically an early warning of the evaluation efficiency between the campus intelligent monitoring cloud platform and the teacher response terminal, and at the same time, an early warning of the evaluation efficiency between the campus intelligent monitoring cloud platform and the parent response terminal.

10. A method for applying the campus interactive data driven student mental health intelligent monitoring system as claimed in any one of claims 1 to 9, characterized in that: include: Collection of mental health assessment data set: The campus intelligent monitoring cloud platform responds to and receives the students’ interactive data, and evaluates the students’ interactive data through the psychological assessment subsystem of the campus intelligent monitoring cloud platform to obtain the students’ mental health assessment data set; Data reception performance improvement determination: obtain the data reception performance information of the teacher terminal and the data reception performance information of the parent terminal, determine the data reception performance evaluation value of the teacher terminal and the data reception performance evaluation value of the parent terminal respectively, and compare them with the data reception performance threshold respectively to obtain the performance comparison result, and determine whether to improve the data reception performance of the teacher terminal and the data reception performance of the parent terminal based on the performance comparison result, and finally record them as the teacher response terminal and the parent response terminal respectively; Data feedback duration factor processing: The teacher response terminal and the parent response terminal receive the student's mental health assessment data set sent by the campus intelligent monitoring cloud platform, thereby obtaining the mental health assessment feedback duration of the teacher response terminal and the mental health assessment feedback duration of the parent response terminal, and obtaining the data feedback duration factor of the teacher response terminal and the data feedback duration factor of the parent response terminal through data processing; Evaluation efficiency index analysis: According to the data feedback time factor of the teacher response terminal and the data feedback time factor of the parent response terminal, the data reception performance evaluation value of the teacher response terminal and the data reception performance evaluation value of the parent response terminal are comprehensively analyzed to analyze the evaluation efficiency index of the campus intelligent monitoring cloud platform, and finally feedback is given to the interactive data evaluation of the campus intelligent monitoring cloud platform.

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