IEEE

A Comparative Study of Driver Drowsiness Detection and Fatigue Analysis using CNN, GAN, and Hardware Models

Abstract: Driver drowsiness and fatigue are significant road safety risks, leading to numerous accidents globally. This research presents a comparative analysis of Convolutional Neural Network (CNN) ...
IEEE

A Lightweight MobileNetV3-FPN Framework for Driver Drowsiness Detection

Abstract: Driver drowsiness remains a major cause of traffic accidents, requiring a drowsiness detection system to achieve high accuracy and real-time inference speed. To overcome these challenges, we ...
IEEE

Driver Drowsiness Detection Using Deep Learning

Abstract: Drowsiness is the main factor that leads to road accidents. Statistics show that drowsy drivers are responsible for accidents. A National Sleep Foundation survey indicates that 20% of ...
IEEE

A Low-Cost IoT Solution for Real-Time Driver Drowsiness Detection using Eye-Blink sensor

Abstract: Drowsy driving is a major cause of road accidents, often leading to severe injuries or fatalities. This paper presents an IoT-based driver drowsiness detection system that monitors eye blink ...
IEEE

An Investigative Comparison of Various Deep Learning Models for Driver Drowsiness Detection

Abstract: Drowsy driving, on its own, presents a significant risk factor for road traffic accidents; most of the time, it results in critical outcomes. This paper describes an advanced driver ...
IEEE

An Investigative Evaluation of Open Source Intrusion Detection Systems for Operational Technology Networks Using MITRE ICS Attack Simulation on a Thermal Power Plant Test Bed

Abstract: Intrusion Detection Systems (IDS) play a critical role in identifying security breaches by monitoring network activities and protecting computer networks and systems. The significant ...