AI-Based Classroom Monitoring System

Abstract: Artificial Intelligence (AI) is transforming education by automating crucial administrative tasks, enhancing student engagement, and improving discipline monitoring. Scholar Insight is an AI-based classroom monitoring system designed to automate attendance tracking, observe student behavior, and provide real- time feedback for educators. Using technologies such as OpenCV, TensorFlow/PyTorch, and NLP, the system detects attendance, monitors engagement, and identifies distractions. The backend is developed with Node.js (Express.js), the database is managed with MongoDB, and the frontend interface is built with React/Next.js. Experimental results indicate 95% accuracy in attendance tracking and 86% accuracy in behavior analysis, significantly reducing manual work for educators. This paper explores the role of AI in increasing student participation and maintaining a disciplined learning environment. Future enhancements include emotion detection and AI-driven learning recommendations.

Keywords: AI in Education, Classroom Monitoring, Facial Recognition, Behavior Analysis, Machine Learning, Deep Learning, Student Engagement, Computer Vision.