An enhanced automated system for evaluating harsh driving using smartphone sensors

Abstract

In this paper we propose an IoT based framework for driving style assessment using the driver owned smartphone as sensing platform. The GPS and the inertial sensors, embedded in the phone are used to continually sample measurements of position, speed and acceleration for the moving vehicle. The required computation is segregated between the phone and a remote server. We present the fusion algorithm which offers accurate estimation of velocity, thereby acceleration and position. To obviate the need for human intervention, an adaptive process in multi-sensor fusion is implemented. Since, the user is not expected to keep the phone in a predefined position and orientation (with respect to the vehicle's longitudinal motion), an automated orientation correction module is essential and is described here.