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Research Article · Open access · Published 7 September 2022

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 & Franck Kalala Mutombo6

Journal of Computer Science, Volume 18, Issue 9, pp. 801–810 · doi.org/10.3844/jcssp.2022.801.810

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Abstract

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.

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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. https://doi.org/10.3844/jcssp.2022.801.810

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A Scalable Big Data Framework for Real-Time Traffic Monitoring SystemJournal of Computer Science · Volume 18, Issue 9 · pp. 801–810 · CC BY 4.0Download