Smart Student Monitoring System

The rapid growth of online education has made it increasingly difficult to ensure academic integrity during remote examinations. To overcome the limitations of traditional manual and webcam-based proctoring, this project presents an AI-Based Smart Student Proctoring System that uses computer vision, behavioral analysis, and real-time activity tracking to automatically monitor students during exams. The system detects suspicious activities such as face absence, multiple persons, gaze deviation, tab switching, and abnormal environmental behavior, generating real-time alerts and detailed violation reports for teachers. By using lightweight, browser-based AI models, the system ensures privacy-preserving and scalable monitoring without requiring additional software installations. The proposed solution provides a secure, efficient, and reliable framework for conducting fair online examinations in modern digital learning environments.