Abstract
In the recent years, mobile devices pervasivity has boosted the diffusion of a novel sensing paradigm known as Mobile Crowd Sensing (MCS). In this paper, we propose a MCS-based system exploiting FIWARE middleware platform and allowing users to gather noise measurements (both opportunistically and participatory) in order to perform large-scale, low-cost and sufficiently accurate urban noise monitoring campaigns. Collected measurements are then aggregated, filtered and interpolated in order to provide city managers with an overview of the actual noise pollution levels in their cities. Specific noise abatement measures are suggested to city managers (in terms of both estimated noise reduction and average installation costs). The already performed field tests demonstrated the feasibility of the proposed approach.
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Pentaho Community Edition: http://community.pentaho.com/projects/data-integration/.
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Acknowledgement
This research activity is part of the EU funded project SP4UM (Grant agreement n. 632853, sub-grant agreement n. 021), within the “frontierCities” FIWARE accelerator.
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Zappatore, M., Longo, A., Bochicchio, M.A., Zappatore, D., Morrone, A.A., De Mitri, G. (2016). Improving Urban Noise Monitoring Opportunities via Mobile Crowd-Sensing. In: Leon-Garcia, A., et al. Smart City 360°. SmartCity 360 SmartCity 360 2016 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 166. Springer, Cham. https://doi.org/10.1007/978-3-319-33681-7_79
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