Driver monitoring is essential as the main reasons for motor vehical accidents is related to driver's inattention or drowsiness. Drowsiness can cause serious road accidents resulting into a threat to life. A drowsiness detector installed on a vehicle can reduce accidents by addressing moment of negligence in real-time. The proposed system aims to assess the drowsiness, fatigue, and distraction accurately by analyzing both eye patterns and eye motion of the driver. The traditional systems can track the driver's eye state, but fail to detect dangerous situations, like a microsleep. Wheareas, the computer vision based system makes it easy to determine the moment of falling asleep, but it needs an additional logic limiting the detection range to prevent increasing a wrong blink detection rate. The proposed approach refines drowsiness detection by analyzing the blink patterns and eye movement to accurately determine when an alarm should be triggered. When drowsiness is detected an alert can be generated by the system through the speakers by playing a beep sound or by displaying an alert message on the display. Further, a system can be integrated with advanced safety features such as emergency breaking to slow down the vehicle when drowsiness is detected.
Driver Drowsiness Detection and Alert System Using Computer Vision
2025-03-07
614231 byte
Conference paper
Electronic Resource
English
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