An Efficient Framework to Detect and Avoid Driver Sleepiness Based on YOLO with Haar Cascades and an Intelligent Agent

In this paper we present a new approach to discern and handle driver's drowsiness. This task is usually based only on its detection, without providing any intelligent feedback appropriated to the situation of the driver, and focusing only on the eyes. The response is usually a simple beep alarm which is not enough to wake up or keep the driver awake all along the road. The innovation in our method resides first in the use of a combination of Haar cascades and deep convolutional neural networks for fast detection of the state of the driver and second, the use of an intelligent assistant agent who will follow up the driver by the front camera of his phone, and tries to take care of his security, and the security of the others.