Road congestion sensing via crowdsourcing and MapReduce

Abstract

Road congestion has become a major problem in cities in developing countries resulting in massive delays, wastage of fuel and road accidents. For proper handling it is essential to observe the road congestion patterns. Methods like on-road cameras, etc. require huge investments whereas crowdsourcing methods generate large amount of redundant data. This paper presents a new approach using event sensing to capture relevant crowdsourced data to estimate road traffic congestion and utilizes MapReduce for generating analytics efficiently.