Paper Title
Driver Drowsiness Detection Using Deep Learning

As a consequence of changes in human time management, the normal sleep cycle of humans is being disrupted in the modern day. As a consequence of inadequate work-life balance, it has become extremely difficult for people to execute tasks such as driving a car, which necessitates good health and a clear mind. The most prevalent cause of road disasters throughout the globe is driver fatigue, which results in him being drowsy. Tiredness is a very frequent issue among drivers, and it may often result in highly serious road accidents. The generation of an alert may be a viable method of preventing a road tragedy caused by drowsy driving on the road. To identify sleepiness, a variety of comprehensive ways are being offered by researchers. As a consequence of this research, we have developed a model that can detect and inform the driver when he or she is feeling sleepy. OpenCV is used in conjunction with the Haar classifier to recognise the face and eyes, and the output is fed into the CNN model. Keywords - Deep Learning, Convolutional Neural Network Driver Drowsiness Detection, Eye Detection