Driver safety remains a critical concern in the automotive industry, with drowsiness and inattention being major contributors to road accidents worldwide. This project focuses on developing an effective safety system designed to monitor driver alertness in real time by detecting eye blinks, a reliable physiological indicator of drowsiness. By continuously estimating the driver’s status through eye blink patterns, the system aims to assess the level of alertness and implement necessary control measures to prevent accidents. The proposed system integrates image processing techniques and real-time monitoring algorithms to accurately track eye movements and identify signs of fatigue. Early detection of drowsiness enables timely warnings or interventions, thus significantly enhancing driving safety. This approach offers a proactive method to reduce accident risks caused by driver fatigue and improve overall road safety. The system’s design ensures adaptability for various lighting conditions and driver behaviors, making it a robust solution for modern vehicles.
Saad Hamed Al-Jabiri (2026) studied this question.