Increasing women's active participation in economic, educational, and social spheres
requires ensuring safe public transport environments. This study investigates the potential of …

This paper introduces a comprehensive framework for the detection of behaviors indicative
of reduced concentration levels among motor vehicle operators, leveraging multimodal …

Driver drowsiness detection is a critical field of research within automotive safety, aimed at
identifying signs of fatigue in drivers to prevent accidents. Drowsiness impairs a driver's …

Nowadays, one of the most common problems faced by Twitter (also known as X) users,
including individuals as well as organizations, is dealing with spam tweets. The problem …

As drowsiness is recognized as one of the primary factors that threaten road safety,
achieving a high-accuracy detection of drowsiness with finer granularity is crucial to …

The increasing global prevalence of global accidents has emphasized the crucial role of
driver alertness in ensuring road safety. This study prioritizes behavioral measurements by …

The escalating prevalence of diabetes globally, exacerbated by lifestyle changes
postpandemic—including increased screen time, sedentary behavior, and remote work …

Drowsiness among drivers is a major hazard to road safety, resulting in innumerable
incidents globally. Despite substantial study, existing approaches for detecting drowsiness …

In this era of information and communication technology (ICT), tremendous improvements
have been witnessed in our daily lives. The impact of these technologies is subjective and …

The use of Convolutional Neural Networks (CNNs) for drowsiness detection is an AI-based
method for detecting and warning of human drowsiness or weariness. Deep learning …