Driver drowsiness detection, also known as driver alertness monitoring, is a car safety technology which helps prevent accidents caused by the driver getting drowsy.

By utilizing computer vision and machine learning techniques, the system aims to detect signs of drowsiness and provide timely alerts — particularly useful for applications like driver monitoring.

May 20, 2025 · By combining cutting-edge deep learning techniques with real-time processing capabilities, this research offers a contactless, reliable, and efficient solution for driver …

The authors built an embedded device for drowsiness detection that used a Raspberry Pi Camera and Raspberry Pi 3 Model B to collect image data, detect the drowsiness level, and alert the …

Nov 27, 2025 · Drowsy driving is a growing cause of traffic accidents, prompting recent exploration of electroencephalography (EEG)-based drowsiness detection systems. However, …

Aug 15, 2025 · Deep learning (DL) models show considerable promise in detecting driver drowsiness, a major contributor to road traffic crashes. This systematic review evaluates the …

Sep 1, 2023 · Many studies have been conducted in the previous to develop a reliable driver drowsiness detection and prediction system that uses a variety of parameters to gauge the …

Can detect if a driver shows first signs of drowsiness by monitoring steering movements and help to avoid crashed caused by fatigue.

We examine the most commonly used techniques for detecting driver drowsiness, such as physiological measures, eye-tracking, and machine learning approaches.

Feb 23, 2022 · Driver drowsiness detection systems can use cameras, eye tracking sensors and other hardware to monitor visual cues, where drowsiness can be detected through yawning …