A review of recent developments in driver drowsiness detection systems

Y Albadawi, M Takruri, M Awad - Sensors, 2022 - mdpi.com
Continuous advancements in computing technology and artificial intelligence in the past
decade have led to improvements in driver monitoring systems. Numerous experimental …

Machine learning and deep learning techniques for driver fatigue and drowsiness detection: a review

SA El-Nabi, W El-Shafai, ESM El-Rabaie… - Multimedia Tools and …, 2024 - Springer
There are several factors for vehicle accidents during driving such as drivers' negligence,
drowsiness, and fatigue. These accidents can be avoided, if drivers are warned in time …

Intelligent driver drowsiness detection for traffic safety based on multi CNN deep model and facial subsampling

M Ahmed, S Masood, M Ahmad… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Facts reveal that numerous road accidents worldwide occur due to fatigue, drowsiness, and
distraction while driving. Few works on the automated drowsiness detection problem …

Low-cost CNN for automatic violence recognition on embedded system

JC Vieira, A Sartori, SF Stefenon, FL Perez… - IEEE …, 2022 - ieeexplore.ieee.org
Due to the increasing number of violence cases, there is a high demand for efficient
monitoring systems, however, these systems can be susceptible to failure. Therefore, this …

Real-time machine learning-based driver drowsiness detection using visual features

Y Albadawi, A AlRedhaei, M Takruri - Journal of imaging, 2023 - mdpi.com
Drowsiness-related car accidents continue to have a significant effect on road safety. Many
of these accidents can be eliminated by alerting the drivers once they start feeling drowsy …

[HTML][HTML] A systematic review on detection and prediction of driver drowsiness

ME Shaik - Transportation research interdisciplinary perspectives, 2023 - Elsevier
Driver drowsiness has emerged as one of the key factors in recent times' traffic accidents,
which can result in fatalities, serious physical losses, large monetary losses, and significant …

[HTML][HTML] IoT-assisted automatic driver drowsiness detection through facial movement analysis using deep learning and a U-Net-based architecture

S Das, S Pratihar, B Pradhan, RH Jhaveri, F Benedetto - Information, 2024 - mdpi.com
The main purpose of a detection system is to ascertain the state of an individual's eyes,
whether they are open and alert or closed, and then alert them to their level of fatigue. As a …

Ensemble deep transfer learning model for Arabic (Indian) handwritten digit recognition

RS Alkhawaldeh, M Alawida, NFF Alshdaifat… - Neural Computing and …, 2022 - Springer
Recognising handwritten digits or characters is a challenging task due to noisy data that
results from different writing styles. Numerous applications essentially motivate to build an …

[HTML][HTML] Structural analysis of driver fatigue behavior: a systematic review

H Zhang, D Ni, N Ding, Y Sun, Q Zhang, X Li - Transportation research …, 2023 - Elsevier
Fatigue is always accompany with the driving task, which have been extensively
investigated for driver monitoring and traffic safety. While many scholars dedicate to the …

Vehicle driver drowsiness detection method using wearable EEG based on convolution neural network

M Zhu, J Chen, H Li, F Liang, L Han… - Neural computing and …, 2021 - Springer
Vehicle drivers driving cars under the situation of drowsiness can cause serious traffic
accidents. In this paper, a vehicle driver drowsiness detection method using wearable …