AI-Based Smart Classroom System for Real-Time Student Behaviour Analysis and Automated Lecture Notes Generation

Abstract

This paper presents an AI-based smart classroom system for real-time student behaviour analysis and automated lecture notes generation. The proposed system integrates Artificial Intelligence, Computer Vision, Machine Learning, and Natural Language Processing techniques to improve classroom monitoring and learning support. The system captures classroom video and lecture audio using cameras and microphones for real-time processing. Student facial expressions, eye movement, and attention levels are analyzed using deep learning algorithms to identify behaviours such as attentive, distracted, confused, and sleepy. Simultaneously, lecture audio is converted into text using speech recognition techniques and summarized automatically using NLP-based methods to generate lecture notes. The generated analytics and reports are displayed through an interactive dashboard for teachers, students, and administrators. Experimental results demonstrate that the proposed system achieves efficient classroom monitoring with approximately 95.2% behaviour analysis accuracy and low latency processing suitable for smart educational environments. The proposed framework improves classroom engagement, reduces manual monitoring effort, and enhances digital learning support.