Description

Drowsiness is a safety hazard in commercial vehicle driving. The conditions to which truck drivers are exposed put them at higher risk as compared to passenger car drivers. Unobtrusive drowsiness detection methods can avoid catastrophic crashes by warning or assisting the drivers. This Process describes an efficient detection system to monitor driver vigilance. An android is used to point directly towards the driver’s face and monitors the driver’s eyes in order to detect drowsiness in about real-time. Image processing technology is involved to analyze images of the driver’s face taken by a regular android. Alertness is detected based on the degree to which the driver’s eyes are open or closed. Several efficient methods are employed to achieve the efficiency. Also we propose the accelerometer based accident detection system based on smart phones. When the smart phone recognize the accelerometer shaking detection then the sensor values are filtered using Kalman filters. Our proposed system has combined both driver drowsiness detection as well as accelerometer based accident alerting system.