Paper Title :Driver Drowsiness Detection with Deep Learning

Author :Omprakash Agrawal, Rahul Mishra, Purvi Tiwari

Article Citation :Omprakash Agrawal ,Rahul Mishra ,Purvi Tiwari , (2023 ) " Driver Drowsiness Detection with Deep Learning " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 71-73, Volume-11,Issue-5

Abstract : Machine learning techniques have been used in order to predict the condition and emotion of a driver to provide information that will improve safety on the road. It is an application of artificial intelligence. Artificial Intelligence is a method by which systems can automatically learn as well as improve without being explicitly programmed. A driver’s condition can be estimated by bio-indicators, behavior while driving as well as the expressions on the face of a driver. In this paper we present an all-inclusive survey of recent works related to driver drowsiness detection and alert system. We also present the various machine learning techniques such as PERCLOS algorithm, HAAR based cascade classifier, OpenCV which are used in order to determine the driver’s condition. Finally, we identify the challenges faced by the current systems and present the corresponding research opportunities. Keyword - Artificial Intelligence, Autonomous Vehicle Technology, Drowsiness Detection, Machine Learning, Face Recognition, Face Detection, Deep Learning, Convolution Neural Network (CNN)

Type : Research paper

Published : Volume-11,Issue-5

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