MELD3: Integrating Multi-Task Ensemble Learning for Driver Distraction Detection

G Azizoglu, AN Toprak - IEEE Access, 2024 - ieeexplore.ieee.org
Detecting and alerting distracted drivers is crucial to prevent traffic accidents. Although
numerous studies have been proposed that use deep learning methods to detect driver …

Internet of things assisted deep learning enabled driver drowsiness monitoring and alert system using CNN-LSTM framework

SP Soman, GS Kumar, SB Nuthalapati… - Engineering …, 2024 - iopscience.iop.org
Driver fatigue has been generally viewed as a critical road safety factor and has been cited
for contributing to a good percentage of traffic accidents. Develo** systems to monitor and …

Enhancing Road Safety: Analyzing Driver Behavior Through AI-Driven Monitoring Techniques

SS Kumar, KRN Vignesh… - 2024 9th International …, 2024 - ieeexplore.ieee.org
This study aims to address the significant threat of safe driving in terms of the characteristics
of drivers, including anger, attention, fatigue, and drowsiness. In an increasingly intelligent …

AI-Driven Wearables for Driver Health and Safety

S Díaz-Santos, P Caballero-Gil… - … Conference on Ubiquitous …, 2024 - Springer
This preliminary research presents a novel driver health monitoring system that aims to
prevent accidents by utilizing wearable devices and artificial intelligence. The system …