Remote education monitoring method and system based on adaptive optimization algorithm

The self-adaptive optimization algorithm-based remote education monitoring system addresses the lack of effective monitoring in remote education by using visual detection to analyze student engagement and provide interventions, enhancing teaching quality.

CN120318772AInactive Publication Date: 2025-07-15SUZHOU ZHONGAO INFORMATION TECH CO LTD
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Patent Information

Application Number
CN202510790360.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-13
Publication Date
2025-07-15
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

The lack of effective monitoring and management in existing distance education has led to difficulties in attendance check-in and difficulty in understanding students' mastery of course knowledge points, which affects the quality of teaching.

Method used

A distance education monitoring method based on adaptive optimization algorithm is adopted to formulate a personalized teaching plan by obtaining student parameter information, and visual detection technology is used to monitor students' body movements and facial expressions in real time, analyze learning status, and generate reminders or alerts to improve concentration.

Benefits of technology

It realizes accurate analysis and real-time monitoring of students' learning status, improves the teaching quality and effectiveness of distance education, promptly discovers learning problems and provides personalized support.

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Abstract

The invention discloses a remote education monitoring method and system based on an adaptive optimization algorithm. The method comprises the following steps: acquiring parameter information of students, making a teaching plan, setting a teaching course, generating a teaching video, establishing a login account based on identity information of the students, and displaying the teaching video. Acquiring learning state information of the student in real time based on a visual detection technology, analyzing the concentration degree of the student based on the learning state information, and judging whether the concentration degree is greater than or equal to a set concentration degree threshold value; if the concentration degree is greater than or equal to the set concentration degree threshold value, continuing to play the teaching video, and scoring the student condition of the student; if the concentration degree is smaller than the set concentration degree threshold value, reminding information is generated, and popup reminding or sound alarming is carried out based on the reminding information; the body movement and facial expression of the student are monitored in real time through the visual detection technology, so that the learning state of the student is accurately analyzed, early warning is performed on the non-focused student according to the learning state of the student, and the effect of remote education is improved.
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