How deep learning enhances real-time drowsiness detection The study presents a sophisticated methodology for detecting driver fatigue using convolutional neural networks (CNNs) and computer vision.

In today’s analysis of traffic accident reports it becomes evident that most driving accidents result from driver drowsiness, fatigue, and lack of alertness. At these moments, drivers cannot react ...

There is a need for the development of a home-use early detection approach characterized by increased reliability and impartiality. A proposed system using ML algorithms for the early detection of PD ...

Citation: Arif S, Munawar S and Ali H (2023) Driving drowsiness detection using spectral signatures of EEG-based neurophysiology. Front. Physiol. 14:1153268. doi: 10.3389/fphys.2023.1153268. Received: ...

This repository provides a Python implementation for detecting drowsiness in real-time using Dlib and OpenCV. The system leverages facial landmarks to calculate the Eye Aspect Ratio (EAR) and Mouth ...