Rafi'e

Real-Time Drowsiness Detection Using Dual MobileNetV2 Models on Desktop and Edge Devices

Drowsiness is a leading cause of human error in transportation and in shift-based occupational work, yet delivering reliable real-time detection on affordable, resource-constrained hardware remains difficult. This study aims to develop and evaluate a vision-based drowsiness detection system that behaves consistently ac...