DROWSINESS DETECTION SYSTEM USING MACHINE LEARNING

DROWSINESS DETECTION SYSTEM USING MACHINE LEARNING

1Naman Jain, 2Mr. Arpit Mishra, 3Khushi Verma

1Student, 2Professor, 3Student

Computer Science and Engineering,

Babu Banarasi Das Northern India Institute Of Technology, Lucknow, Uttar Pradesh, India

worknj15@gmail.com, kv92431@gmail.com

Abstract— The Drowsiness Detection System (DDS) is an innovative solution designed to detect and prevent accidents caused by drowsy driving. By combining computer vision and machine learning techniques, the DDS continuously monitors the driver's eyes in real-time. The system captures video frames, detects faces, and analyzes the eye regions to determine if the eyes are open or closed. Using a scoring mechanism, the DDS assesses the driver's level of drowsiness, and when it exceeds a threshold, an alarm is triggered to alert the driver. With its ability to detect early signs of drowsiness, the DDS enhances road safety by providing timely warnings to drivers, mitigating the risks associated with drowsy driving.

Index Terms—Machine learning , Deep learning, Convolutional Neural Network.