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With the continuous advancement of information technology, remote education exams are facing increasingly diverse cheating methods, and traditional monitoring methods are no longer sufficient to cope with these challenges. This study aims to design and implement a comprehensive anti-cheating system for exams. The core of this system is an intelligent monitoring system that integrates head posture recognition and eye tracking technologies. By monitoring the multidimensional behavior of examinees, it effectively identifies and prevents cheating behaviors. The system also enhances security through functions such as anti-screenshot, disabling clipboard, and preventing remote answering. Through practical application testing, the system can effectively identify and prevent various cheating methods, significantly improving the monitoring efficiency and fairness of remote exams. This research provides a comprehensive and effective technical solution for modern educational exam supervision, which is of great significance in improving the security and fairness of remote online exams.
zheng et al. (Thu,) studied this question.
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