Abstract
There is a growing possibility of drivers engaging in disruptive behaviors with increasingly regular in-vehicle technologies and transported devices. As a consequence, diversion and carelessness are adding to the likelihood of a collision and have a growing effect on driving health. To alleviate these concerns, this study discusses the usage of a dashboard camera to accurately identify distracted drivers utilizing a machine learning methodology. Then we use Image net models like VGG16, RESNET50, Xception and Mobile net to predict the rate of performance analysis of driver detection. Also this study implemented an alert system procedure of distracted driver prediction using machine learning techniques.
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