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Article Dans Une Revue Procedia Computer Science Année : 2017

Deploying Real Time Big Data Analytics in Cloud Ecosystem for Hazmat Stochastic Risk Trajectories

Résumé

The transport of hazardous materials (HazMat) is regulated by a legal framework in line with international standards, in particular the European Agreement concerning the international Accord for Dangerous goods by Road (ADR) which entered in Morocco in June 2011-BO 5956 bis, 30.6.2011. In this work, we propose a model for calculating the risk exposure of the transport of hazardous materials (THM) trajectories using the Gaussian stochastic travel time. The THD trajectory meta-model is extended to take into account the risk management dimension. The storage of the TMD trajectories is used for discovering risk patterns on the urban space by means of the mesh of Voronoi. The proposed analytical solution is deployed in an interoperable infrastructure using intelligent transport systems architecture

Dates et versions

hal-02021594 , version 1 (16-02-2019)

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Lamia Karim, Azedine Boulmakoul, Aziz Mabrouk, Ahmed Lbath. Deploying Real Time Big Data Analytics in Cloud Ecosystem for Hazmat Stochastic Risk Trajectories. Procedia Computer Science, 2017, 8th International Conference on Ambient Systems, Networks and Technologies (ANT) / 7th International Conference on Sustainable Energy Information Technology (SEIT) May 2017 Madeira, 109, pp.180-187. ⟨10.1016/j.procs.2017.05.322⟩. ⟨hal-02021594⟩
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