Driver Distraction Estimation Through AdaBoost and IOT

The safety of the roads is highly important for the purpose of reducing the fatalities and casualties that are caused due to it. Extensive study shows that most of the mishaps caused on the road are due to driver distraction or alcohol intoxication that can lead to impaired driving and reaction times which can be a recipe for disaster on the road. The obstacles on the road also play an important part in leading to collisions which can be an unforeseen scenario that can be easily prevented through the use of effective methodologies. Most of the predominant researchers utilize in invasive approach for the purpose of driver distraction detection which does more harm than good. Therefore for the purpose of achieving an effective driver distraction driver intoxication and obstacle detection an effective methodology has been elaborated in this research article. The proposed methodology utilizes ultrasonic sensors along with the use of image processing techniques strengthened by adaboost and decision tree approach for effective and accurate driver distraction detection along with driver intoxication as well as obstacle detection. The approach has been effectively experimented on to achieve the performance metrics which indicates a satisfactory performance of the approach.