Research Article Open Access

A Scalable Big Data Framework for Real-Time Traffic Monitoring System

Wilfried Yves Hamilton Adoni1,2, Najib Ben Aoun3,4, Tarik Nahhal2, Moez Krichen3,5, Mohammed Y. Alzahrani3 and Franck Kalala Mutombo6
  • 1 Engineering School, International University of Casablanca, Casablanca, Morocco
  • 2 FDMS Research Unit, Hassan II University of Casablanca, Casablanca, Morocco
  • 3 College of Computer Science and Information Technology, Al Baha University, Al Baha, Saudi Arabia
  • 4 REGIM-Lab Research Groups in Intelligent Machines, University of Sfax, Sfax, Tunisia
  • 5 ReDCAD Laboratory, University of Sfax, Sfax, Tunisia
  • 6 Department of Mathematics, University of Lubumbashi, Lubumbashi, Democratic Republic Of Congo


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.

Journal of Computer Science
Volume 18 No. 9, 2022, 801-810


Submitted On: 2 June 2022 Published On: 7 September 2022

How to Cite: Adoni, W. Y. H., Aoun, N. B., Nahhal, T., Krichen, M., Alzahrani, M. Y. & Mutombo, F. K. (2022). A Scalable Big Data Framework for Real-Time Traffic Monitoring System. Journal of Computer Science, 18(9), 801-810.

  • 5 Citations



  • Road Sensor
  • GPS Sensor
  • Intelligent Transportation System
  • Big Data
  • Smart City
  • Traffic Monitoring
  • Urban Mobility
  • Hadoop
  • IBM InfoSphere