TY  - JOUR
AU  - Adoni, Wilfried Yves Hamilton 
AU  - Aoun, Najib Ben 
AU  - Nahhal, Tarik 
AU  - Krichen, Moez 
AU  - Alzahrani, Mohammed Y. 
AU  - Mutombo, Franck Kalala 
PY  - 2022
TI  - A Scalable Big Data Framework for Real-Time Traffic Monitoring System
JF  - Journal of Computer Science
VL  - 18
IS  - 9
DO  - 10.3844/jcssp.2022.801.810
UR  - https://thescipub.com/abstract/jcssp.2022.801.810
AB  - Inthis study, a scalable and real-time intelligent transportation system based ona big data framework is presented. The proposed system allows for the use ofexisting data from road sensors to better understand traffic flow, and travelerbehavior and increase road network performance. Our transportation system isdesigned to process large-scale stream data to analyze traffic events such asincidents, crashes, and congestion. The experiments performed on the publictransportation modes of the city of Casablanca in Morocco reveal that theproposed system achieves a significant gain of time, gathers large-scale datafrom many road sensors, and is not expensive in terms of hardware resourceconsumption.