sc 17(5): e3

Research Article

A distributed platform for big data analysis in smart cities: combining Intelligent Transportation Systems and socioeconomic data for Montevideo, Uruguay

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  • @ARTICLE{10.4108/eai.19-12-2017.153478,
        author={Sergio Nesmachnow and Sebasti\^{a}n  Ba\`{o}a and Renzo Massobrio},
        title={A distributed platform for big data analysis in smart cities: combining Intelligent Transportation Systems and socioeconomic data for Montevideo, Uruguay},
        journal={EAI Endorsed Transactions on Smart Cities},
        volume={2},
        number={5},
        publisher={EAI},
        journal_a={SC},
        year={2017},
        month={12},
        keywords={Smart cities, big data, distributed computing, Intelligent Transportation Systems},
        doi={10.4108/eai.19-12-2017.153478}
    }
    
  • Sergio Nesmachnow
    Sebastián Baña
    Renzo Massobrio
    Year: 2017
    A distributed platform for big data analysis in smart cities: combining Intelligent Transportation Systems and socioeconomic data for Montevideo, Uruguay
    SC
    EAI
    DOI: 10.4108/eai.19-12-2017.153478
Sergio Nesmachnow1,*, Sebastián Baña1, Renzo Massobrio1
  • 1: Universidad de la República, Herrera y Reissig 565, Montevideo, Uruguay
*Contact email: sergion@fing.edu.uy

Abstract

This article proposes a platform for distributed big data analysis in the context of smart cities. Extracting useful mobility information from large volumes of data is crucial to improve decision-making processes in smart cities. This article introduces a framework for mobility analysis in smart cities combining Intelligent Transportation Systems and socioeconomic data for the city of Montevideo, Uruguay. The efficiency of the proposed system is analyzed over a distributed computing infrastructure, demonstrating that the system scales properly for processing large volumes of data for both off-line and on-line scenarios. Applications of the proposed platform and case studies using real data are presented, as examples of the valuable information that can be offered to both citizens and authorities. The proposed model for big data processing can also be extended to allow using other distributed (e.g. grid, cloud, fog, edge) computing infrastructures.