VISIONSAFE: OPENCV-POWERED DRIVER FATIGUE DETECTION SYSTEM
DOI:
https://doi.org/10.64751/Abstract
Driver drowsiness is a leading cause of road accidents, posing significant risks to traffic safety worldwide. This study presents VisionSafe, a real-time driver fatigue detection framework utilizing OpenCV algorithms to monitor facial features and eye behavior for early signs of sleepiness. By analyzing parameters such as eye closure rate, blink frequency, and head orientation, the system identifies fatigue patterns and generates timely alerts to prevent accidents. The proposed framework leverages computer vision techniques, including face detection, eye tracking, and motion analysis, to ensure accuracy under varying lighting and driving conditions. Experimental evaluation demonstrates that VisionSafe achieves high detection precision and responsiveness, providing an effective and practical solution for enhancing driver safety. The study highlights the potential of integrating computer vision with automotive safety systems to reduce fatigue-related accidents and improve overall road safety
