Driver Drowsiness Detection System with OpenCV & Keras

Nowadays, transport facility is a basic component of living. While driving, any one of us can come across an accident, that may be due to lack of sleep, uneven physical health, or prolonged travelling. The lack of sleep or any unfair condition deviates from a higher chance of accidents. The weakness or sluggishness are among the major causes for road accidents. Due to this, there is a higher number of accidents annually across the globe. There have been several vehicle’s accidents across the globe in recent years. Several vehicles are running over the road day and night. Due to continuous travelling, it becomes obvious to get tired and the same can be measured in terms of drowsiness. Due to lack of sleep, it becomes very dangerous to drive. Hence, it is an urgent need to catch the fatigue nature of the motorist to protect his survival as well as of others. Driver Drowsiness Detection System is the main target of this paper. This model captures images of the driver in real time without stopping and measures the state of the driver’s eyes using particular algorithms. Though there are several other methods to do the same task this method is completely disconnected from the driver as it does not affect the driver in any manner. For recognizing somnolence, the stopping score of the eyes is measured and if it goes beyond a given score then one is considered sleepy and in-that case, an alarm is raised by the system immediately.