Abstract: Systems to identify tiredness in drivers are becoming more widely recognized as essential safety innovations intended to reduce accidents brought on by fatigued drivers. This paper delivers ...

Abstract: Detection of drowsiness in drivers is a crucial aspect to improve road safety and reduce traffic accidents. This study evaluates the comparative performance of the latest object detection ...

Abstract: Electromyography (EMG) signals are extensively investigated inputs for driver drowsiness detection algorithms due to its ability to monitor muscle activity. However, the use of facial muscle ...

Abstract: Driver fatigue is a leading cause of traffic accidents, underscoring the urgent need for advanced fatigue detection systems. The integration of physiological signals, especially ...

Abstract: Drowsiness-related Road accidents are becoming more common, highlighting the need for effective driver monitoring systems. This paper introduces a real-time drowsiness detection system using ...

Abstract: Driver behavior monitoring is essential for advancing driver assistance systems, particularly in detecting highrisk or distracted actions. This study introduces ResBoot-50, an enhanced ...

Abstract: In today’s world Driver drowsiness is a major cause of road accidents, necessitating the development of robust and accurate drowsiness detection systems. Traditional single-feature ...

Abstract: Distracted driving is a significant cause of road accidents worldwide, so innovative solutions for effective detection and prevention are needed. This study explores recent advancements in ...

Abstract: Ensuring driver alertness is essential for road safety, as fatigue-related accidents significantly contribute to global traffic fatalities. Prolonged driving, lack of rest, and monotonous ...