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Mobile crowdsensing for road sustainability: exploitability of publicly-sourced data

Lorenz Cuno Klopfenstein, Saverio Delpriori, Paolo Polidori, Andrea Sergiacomi, Marina Marcozzi, Donna Boardman, Peter Parfitt and Alessandro Bogliolo

International Review of Applied Economics, 2020, vol. 34, issue 5, 650-671

Abstract: This paper examines the opportunities and the economic benefits of exploiting publicly-sourced datasets of road surface quality. Crowdsourcing and crowdsensing initiatives channel the participation of engaged citizens into communities that contribute towards a shared goal. In providing people with the tools needed to positively impact society, crowd-based initiatives can be seen as purposeful drivers of social innovation from the bottom. Mobile crowdsensing (MCS), in particular, takes advantage of the ubiquitous nature of mobile devices with on-board sensors to allow large-scale inexpensive data collection campaigns. This paper illustrates MCS in the context of road surface quality monitoring, presenting results from several pilots adopting a public crowdsensing mobile application for systematic data collection. Evaluation of collected information, its quality, and its relevance to road sustainability and maintenance are discussed, in comparison to authoritative data from a variety of other sources.

Date: 2020
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DOI: 10.1080/02692171.2019.1646223

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Handle: RePEc:taf:irapec:v:34:y:2020:i:5:p:650-671