Title: Cloud big data application for transport

Authors: Gavin Kemp; Genoveva Vargas-Solar; Catarina Ferreira Da Silva; Parisa Ghodous; Christine Collet; Pedro Pablo Lopez Amalya

Addresses: LIRIS, CNRS, Université Lyon 1, UMR5202, Bd du 11 Novembre 1918, Villeurbanne, F69621, France ' Grenoble Institute of Technology, CNRS, LIG-LAFMIA, 681 rue de la Passerelle, Saint Martin d'Hères, F38401, France ' LIRIS, CNRS, Université Lyon 1, UMR5202, Bd du 11 Novembre 1918, Villeurbanne, F69621, France ' LIRIS, CNRS, Université Lyon 1, UMR5202, Bd du 11 Novembre 1918, Villeurbanne, F69621, France ' Grenoble Institute of Technology, CNRS, LIG, 681 rue de la Passerelle, Saint Martin d'Hères, F38401, France ' LIRIS, CNRS, Université Lyon 1, UMR5202, Bd du 11 Novembre 1918, Villeurbanne, F69621, France

Abstract: This paper presents a cloud service oriented approach for managing and analysing big data required by transport applications. Big data analytics brings new insights and useful correlations of large data collections providing undiscovered knowledge. Applying it to transport systems brings better understanding to the transport networks revealing unexpected choking points in cities. This facility is still largely inaccessible to small companies due to their limited access to computational resources. A cloud-oriented architecture opens new perspectives for providing efficient and personalised big data management and analytics services to (small) companies.

Keywords: intelligent transport systems; ITS; big data analytics; cloud services; NoSQL; cloud computing; transport networks; choke points; bottlenecks; personalisation; big data management; small firms.

DOI: 10.1504/IJASM.2016.079940

International Journal of Agile Systems and Management, 2016 Vol.9 No.3, pp.232 - 250

Received: 05 Dec 2015
Accepted: 23 May 2016
Published online: 22 Oct 2016 *

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