Real-time Driver Drowsiness Detection Techniques using Machine Learning Algorithms and Models

Abstract

This paper is a report on the research conducted in the field of electronics and communication engineering to develop a system for driver drowsiness detection to prevent accidents happening because of driver fatigue and sleepiness. The document discusses the solution by Tensor flow machine learning tool and open CV image pre-processing available for detecting fatigue and their efficacy in preventing accidents in the current state of traffic. Furthermore, the paper states the overview of the observations made by the authors in order to help further optimization in the mentioned field to achieve the utility at a better efficiency for a safer road. Key Words: Deep Learning, Convolutional Neural Networks (CNNs), Real-time Monitoring, Facial Feature Analysis, Eye Closure Detection, EEG Signal Analysis