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Smart city article details

Title	A Scalable Big Data Framework For Real-Time Traffic Monitoring System
ID_Doc	4398
Authors	Adoni W.Y.H.; Aoun N.B.; Nahhal T.; Krichen M.; Alzahrani M.Y.; Mutombo F.K.
Year	2022
Published	Journal of Computer Science, 18, 9
DOI	http://dx.doi.org/10.3844/jcssp.2022.801.810
Abstract	In this study, a scalable and real-time intelligent transportation system based on a big data framework is presented. The proposed system allows for the use of existing data from road sensors to better understand traffic flow, and traveler behavior and increase road network performance. Our transportation system is designed to process large-scale stream data to analyze traffic events such as incidents, crashes, and congestion. The experiments performed on the public transportation modes of the city of Casablanca in Morocco reveal that the proposed system achieves a significant gain of time, gathers large-scale data from many road sensors, and is not expensive in terms of hardware resource consumption. © 2022 Wilfried Yves Hamilton Adoni, Najib Ben Aoun, Tarik Nahhal, Moez Krichen, Mohammed Y. Alzahrani and Franck Kalala Mutombo. This open-access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
Author Keywords	Big data; Gps sensor; Hadoop; Ibm infosphere; Intelligent transportation system; Road sensor; Smart city; Traffic monitoring; Urban mobility

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