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sc 16(1): e3

Research Article

A Mobile Crowd-Sensing Platform for Noise Monitoring in Smart Cities

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  • @ARTICLE{10.4108/eai.18-7-2016.151627,
        author={M. Zappatore and A. Longo and M.A. Bochicchio and D. Zappatore and A.A. Morrone and G. De Mitri},
        title={A Mobile Crowd-Sensing Platform for Noise Monitoring in Smart Cities},
        journal={EAI Endorsed Transactions on Smart Cities},
        volume={1},
        number={1},
        publisher={EAI},
        journal_a={SC},
        year={2016},
        month={7},
        keywords={},
        doi={10.4108/eai.18-7-2016.151627}
    }
    
  • M. Zappatore
    A. Longo
    M.A. Bochicchio
    D. Zappatore
    A.A. Morrone
    G. De Mitri
    Year: 2016
    A Mobile Crowd-Sensing Platform for Noise Monitoring in Smart Cities
    SC
    EAI
    DOI: 10.4108/eai.18-7-2016.151627
M. Zappatore1,*, A. Longo1, M.A. Bochicchio1, D. Zappatore1, A.A. Morrone1, G. De Mitri1
  • 1: Dept. of Innovation Engineering, Univ. of Salento, via Monteroni sn, 73100 Lecce, Italy
*Contact email: marcosalvatore.zappatore@unisalento.it

Abstract

Modern cities are moving towards novel approaches for urban sustainability for improving citizenship’s life quality, thus aiming at the Smart City model. Environmental and mobility issues represent two key areas where policy makers address their interventions and, amongst them, noise pollution is one of the most significant causes of public concern. However, noise monitoring campaigns are expensive and require skilled personnel. A viable alternative is represented by Mobile Crowd Sensing (MCS) paradigm, which exploits mobile devices as sensing platforms. In this paper, we propose a MCS-based platform that exploits noise measurements collected by citizens and offers a suggestion system to city managers about noise abatement measures (in terms of both estimated noise reduction and average installation costs). Several field tests demonstrated the feasibility of this approach as a suitable way to support city managers and to widen the possibilities of collaborative urban noise monitoring.

Received
2015-11-30
Accepted
2016-04-29
Published
2016-07-20
Publisher
EAI
http://dx.doi.org/10.4108/eai.18-7-2016.151627

Copyright © 2016 M. Zappatore et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.

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