Applicability of Big Data Techniques to Smart Cities Deployments

M. Victoria Moreno; Fernando Terroso-Saenz; Aurora Gonzalez-Vidal; Mercedes Valdes-Vela; Antonio F. Skarmeta; Miguel A. Zamora; Victor Chang

doi:10.1109/TII.2016.2605581

Applicability of Big Data Techniques to Smart Cities Deployments

M. Victoria Moreno^*
, Fernando Terroso-Saenz
, Aurora Gonzalez-Vidal
, Mercedes Valdes-Vela
, Antonio F. Skarmeta
, Miguel A. Zamora
, Victor Chang

^*Corresponding author for this work

International Business School Suzhou

University of Murcia

Research output: Contribution to journal › Article › peer-review

128 Citations (Scopus)

Abstract

This paper presents the main foundations of big data applied to smart cities. A general Internet of Things based architecture is proposed to be applied to different smart cities applications. We describe two scenarios of big data analysis. One of them illustrates some services implemented in the smart campus of the University of Murcia. The second one is focused on a tram service scenario, where thousands of transit-card transactions should be processed. Results obtained from both scenarios show the potential of the applicability of this kind of techniques to provide profitable services of smart cities, such as the management of the energy consumption and comfort in smart buildings, and the detection of travel profiles in smart transport.

Original language	English
Pages (from-to)	800-809
Number of pages	10
Journal	IEEE Transactions on Industrial Informatics
Volume	13
Issue number	2
DOIs	https://doi.org/10.1109/TII.2016.2605581
Publication status	Published - Apr 2017

Keywords

Big data
Internet of Things (IOT)
predictive models
smart city
transit-card mining

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10.1109/TII.2016.2605581

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title = "Applicability of Big Data Techniques to Smart Cities Deployments",

abstract = "This paper presents the main foundations of big data applied to smart cities. A general Internet of Things based architecture is proposed to be applied to different smart cities applications. We describe two scenarios of big data analysis. One of them illustrates some services implemented in the smart campus of the University of Murcia. The second one is focused on a tram service scenario, where thousands of transit-card transactions should be processed. Results obtained from both scenarios show the potential of the applicability of this kind of techniques to provide profitable services of smart cities, such as the management of the energy consumption and comfort in smart buildings, and the detection of travel profiles in smart transport.",

keywords = "Big data, Internet of Things (IOT), predictive models, smart city, transit-card mining",

author = "Moreno, \{M. Victoria\} and Fernando Terroso-Saenz and Aurora Gonzalez-Vidal and Mercedes Valdes-Vela and Skarmeta, \{Antonio F.\} and Zamora, \{Miguel A.\} and Victor Chang",

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AU - Moreno, M. Victoria

AU - Terroso-Saenz, Fernando

AU - Gonzalez-Vidal, Aurora

AU - Valdes-Vela, Mercedes

AU - Skarmeta, Antonio F.

AU - Zamora, Miguel A.

AU - Chang, Victor

PY - 2017/4

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AB - This paper presents the main foundations of big data applied to smart cities. A general Internet of Things based architecture is proposed to be applied to different smart cities applications. We describe two scenarios of big data analysis. One of them illustrates some services implemented in the smart campus of the University of Murcia. The second one is focused on a tram service scenario, where thousands of transit-card transactions should be processed. Results obtained from both scenarios show the potential of the applicability of this kind of techniques to provide profitable services of smart cities, such as the management of the energy consumption and comfort in smart buildings, and the detection of travel profiles in smart transport.

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KW - predictive models

KW - smart city

KW - transit-card mining

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JF - IEEE Transactions on Industrial Informatics

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Applicability of Big Data Techniques to Smart Cities Deployments

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Keywords

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