Edutrack Smart System

Abstract: The rapid advancement of smart educational technologies has enabled the development of intelligent classroom environments that enhance both administrative efficiency and learning quality. This paper proposes an integrated smart classroom system that combines embedded hardware with computer vision-based analytics to automate attendance and measure student engagement. The system utilizes an Arduino Uno microcontroller connected to an LCD display for real- time timetable visualization, while a Python-based web application manages student data and lecture sessions. A key contribution of this work is the introduction of a concentration-based attendance mechanism, where students are marked present only if they maintain visual engagement for at least 75% of the lecture duration. A vision module continuously processes video frames using face detection and recognition techniques to track student presence and attention over time. Experimental evaluation demonstrates that the system achieves high accuracy in attendance tracking while effectively reducing proxy attendance. The integration of real-time analytics and visualization further enhances faculty decision- making. This system provides a scalable and cost-effective solution for modern smart classrooms. This integration of IoT-enabled hardware and AI-driven analytics provides a unified and practical solution for modern smart classroom environments.

Keywords: Smart Classroom, Automated Attendance System, Face Recognition, Computer Vision, Student Engagement Analysis, Concentration-Based Attendance, Internet of Things, IoT, Arduino Uno, Real-Time Monitoring, Human- Computer Interaction.