NEXTZEN CLASSROOM MANAGEMENT SOFTWARE

Abstract

Recent progress in artificial intelligence and computer vision has created new possibilities for automating routine classroom management activities. Traditional attendance methods and manual supervision of student behavior often consume valuable teaching time and are susceptible to mistakes and inconsistencies. This study presents the development of a Smart Classroom Management System designed to streamline classroom administration through automation and real-time monitoring. The proposed solution combines facial recognition technology for automatic attendance marking with an object detection model capable of identifying mobile phone usage during lectures.The system is implemented as a web-based platform using Python and the Django framework, enabling seamless integration of computer vision models into everyday classroom operations. By leveraging deep learning techniques, the platform can capture live video streams, recognize registered students, record attendance instantly, and detect prohibited device usage. Additionally, an automated notification feature sends timely email alerts to faculty members and parents regarding absenteeism and classroom policy violations. Experimental evaluation indicates that the system performs reliably in real-time scenarios, improves operational efficiency, and enhances transparency in academic environments.