Analysis and Implementation of Driver Drowsiness, Distraction, and Detection System

This work presented analysis and implementation of driver drowsiness, distraction, and detection systems using image processing techniques. The literature review based on drowsiness, distraction, and detection have been taken with their parameters in tabulation form. Flow charts of software and hardware have been presented for the proposed architecture. A comparative analysis of parameters with their percentage of accuracy is given in the table. Therefore, the proposed system found better accuracy as compared to other results. After practically implementation, this system gives the accurate results for the detection of sleepiness of driver. It detects the driver’s state such as Sleepy, Drowsy & Active. The proposed work found accuracy in term of parameter like: eye detection accuracy is 95% and drowsiness accuracy is 90%, it is approximately around 5–7% more accurate as compare to other existing work.