Driver Monitoring System: Enhancing Road Safety through Machine Learning and Computer Vision

Driver inattention and drowsiness are major contributors to road accidents, causing significant loss of life and property globally. This research aims to develop an intelligent Driver Monitoring System (DMS) leveraging advanced machine learning and computer vision techniques to enhance road safety. The proposed system employs real-time facial analysis and behavioral monitoring to detect signs of driver distraction and fatigue. By utilizing a lightweight MobileNetV2-based architecture, the system achieves high accuracy while maintaining computational efficiency, ensuring it can operate in resource-constrained environments. This paper discusses the system’s objectives, algorithm, implementation and validation, highlighting its potential to significantly improve road safety and align with global initiatives for accident prevention.