A deep learning-based real-time driver drowsiness detection and alert system using CNN-LSTM architecture. The model analyzes eye movements, mouth openness (yawning), and head pose to accurately ...

A real-time Driver Drowsiness Detection System built using Python, OpenCV, MediaPipe, and Django. The system monitors the driver's eyes through a webcam and detects drowsiness based on eye movement ...

This research addresses the challenge of monitoring railway driver drowsiness using a real-time, vision-based system powered by convolutional neural networks, specifically the YOLOv8 architecture ...

Abstract: One of the main causes of traffic accidents is fatigued drivers. This study aims to create a real-time, non-intrusive system that employs computer vision techniques to identify driver ...

School of Chemistry and Biochemistry, College of Sciences, and Parker H. Petit Institute for Bioengineering and Biosciences (IBB), Georgia Institute of Technology (GaTech), Atlanta, Georgia 30332, ...

The fatality of road accidents in this era is alarming. According to WHO, approximately 1.30 million people die each year in road accidents. Road accidents result in significant socioeconomic losses ...

Frequent nightly arousals typical for sleep disorders cause daytime fatigue and present health risks. As such arousals are often short, partial, or occur locally within the brain, reliable ...