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

Journal of computer sciences

article

Wilfried Yves Hamilton Adoni¹  Najib Ben Aoun³  Tarik Nahhal²  Moez Krichen³  Mohammed Y. Alzahrani³  Franck Kalala Mutombo⁵ 

[1] Engineering School, International University of Casablanca;FDMS Research Unit, Hassan II University of Casablanca;College of Computer Science and Information Technology, Al Baha University;REGIM-Lab Research Groups in Intelligent Machines, University of Sfax;Department of Mathematics, University of Lubumbashi

关键词: Road Sensor;    GPS Sensor;    Intelligent Transportation System;    Big Data;    Smart City;    Traffic Monitoring;    Urban Mobility;    Hadoop;    IBM InfoSphere;   

DOI  :  10.3844/jcssp.2022.801.810

学科分类：计算机科学（综合）

来源: Science Publications

【 摘 要 】

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.

【 授权许可】

CC BY