AI Based Student Drift Detection System

Student attention and concentration play an important role in academic performance. In online learning environments and smart classrooms, monitoring student focus manually is difficult and time-consuming. This paper proposes an AI Based Student Drift Detection System using Camera Monitoring and Alert Sound to automatically identify students who lose concentration during learningsessions.The system uses a webcam to continuously monitor the student’s face, eye movement, and head posture. Artificial Intelligence techniques such as Computer Vision, Machine Learning, and Deep Learning are used to detect inattentive behavior like sleeping, looking away, excessive head movement, and absence from the screen. When the system detects drift in student attention for a specific duration, it generates an automatic alert sound to regain studentfocus.

Keypoints — Artificial Intelligence, Student Drift Detection, Computer Vision, Deep Learning, Camera Monitoring, Alert Sound, Face Detection