Drivers who do not take regular breaks when driving long distances run a high risk of becoming drowsy a state which they often fail to recognize early enough according to the experts. Studies show that around one quarter of all serious motorway accidents are attributable to sleepy drivers in need of a rest, meaning that drowsiness causes more road accidents than drink-driving. Attention assist ...

The aim of our project is to provide a real time non-intrusive driver drowsiness detection to prevent the rapidly growing accidents caused by sleepy or drunk driver. We are going to merge the 2 requirements for safe driving in a single equipment. The car does not function unless the two conditions of safe driving are satisfied. Bio signals, such as brain waves, pulsation waves, and heart beat a...

The proposed system aims to lessen the number of accidents that occur due drivers’ drowsiness and fatigue, which will in turn increase transportation safety. This is becoming a common reason for recent times. Several faces body gestures are considered such as signs fatigue drivers, including tiredness eyes yawning. These features an indication driver’s condition improper. EAR (Eye Aspect Ratio)...

The advance of computing technology has provided the means for building intelligent vehicle systems. Drowsy driver detection system is one of the potential applications of intelligent vehicle systems. Previous approaches to drowsiness detection primarily make pre-assumptions about the relevant behavior, focusing on blink rate, eye closure, and yawning. Here we employ machine learning to data-mi...

now a day’s Road accidents are common in developed as well as developing countries. These accidents happen due to different different reasons like sleeping disorders, working in night shift or more than eight hours as over time, side effects of medicine, alcohol, speeding, freakishness of teenager’s etc. One of the most important reasons is drowsiness. Drowsiness means sleepiness, which affects...

Today most accidents are caused by drivers’ fatigue, drowsiness and losing attention on the road ahead. In this paper, a system is introduced, using RGB-D cameras to automatically identify drowsiness and give warning. In this system two important modules have been utilized simultaneously to identify the state of driver’s mouth and eyes for detecting drowsiness. At first, using the depth informa...