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Crowd-Sourced Data Collection for Urban Monitoring via Mobile Sensors

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Published:26 October 2017Publication History
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Abstract

A considerable amount of research has addressed Internet of Things and connected communities. It is possible to exploit the sensing capabilities of connected communities, by leveraging the continuously growing use of cloud computing solutions and mobile devices. The pervasiveness of mobile sensors also enables the Mobile Crowd Sensing (MCS) paradigm, which aims at using mobile-embedded sensors to extend monitoring of multiple (environmental) phenomena in expansive urban areas. In this article, we discuss our approach with a cloud-based platform to pave the way for applying crowd sensing in urban scenarios. We have implemented a complete solution for environmental monitoring of several pollutants, like noise, air, electromagnetic fields, and so on in an urban area based on this paradigm. Through extensive experimentation, specifically on noise pollution, we show how the proposed infrastructure exhibits the ability to collect data from connected communities, and enables a seamless support of services needed for improving citizens’ quality of life and eventually helps city decision makers in urban planning.

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              • Published in

                cover image ACM Transactions on Internet Technology
                ACM Transactions on Internet Technology  Volume 18, Issue 1
                Special Issue on Connected Communities
                February 2018
                250 pages
                ISSN:1533-5399
                EISSN:1557-6051
                DOI:10.1145/3155100
                • Editor:
                • Munindar P. Singh
                Issue’s Table of Contents

                Copyright © 2017 ACM

                Publisher

                Association for Computing Machinery

                New York, NY, United States

                Publication History

                • Published: 26 October 2017
                • Accepted: 1 May 2017
                • Revised: 1 February 2017
                • Received: 1 May 2016
                Published in toit Volume 18, Issue 1

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