E-WAY APPROACH TO SENSE THE ROAD CONDITION USING MACHINE LEARNING

Abstract

Monitoring road & traffic conditions in a city is a problem widely studied. Several methods have been proposed for addressing this problem. Several proposed techniques require dedicated hardware such as GPS-devices and acce-lerometers in vehicles or cameras on the road-side and near traffic signals. All such methods are expensive in terms of monetary cost and human effort required. We propose a notion- intrusive method that uses sensors present on smartphones. In the proposed system, we use an acce-lerometer, GPS sensor readings for traffic and road conditions detection. We are specifically interested in identifying braking events - frequent braking indicates congested traffic conditions - and bumps on the roads to characterize the type of road.