COMPUTER VISION FOR ATTENDENCE TRACKING AND EMOTION MONITORING IN SCHOOL SETTINGS

Computer Engineering

This paper introduces a novel computer vision system designed to automate attendance tracking and monitor student emotions in school settings. The system leverages advanced facial recognition algorithms to identify students and track their attendance. In addition, it employs emotion detection algorithms to analyze students' facial expressions, providing real-time insights into their emotional states during class. The primary aim of this system is to enhance the learning environment by ensuring regular attendance and addressing students' emotional well-being, both of which are critical factors in academic success. Initial experiments with the system have demonstrated promising results, with high levels of accuracy and efficiency in both attendance tracking and emotion monitoring. These results suggest that our system could serve as a valuable tool for educators and school administrators, helping them to better understand and respond to students' needs. Looking ahead, our future work will focus on improving the robustness of our system in diverse lighting and environmental conditions. We also plan to explore the potential for integrating our system with existing educational management systems, with the goal of providing a comprehensive solution for managing student attendance and well-being.

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