Mobile crowdsensing for road sustainability: exploitability of publicly-sourced data
Lorenz Cuno Klopfenstein,
Peter Parfitt and
International Review of Applied Economics, 2020, vol. 34, issue 5, 650-671
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.
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Persistent link: https://EconPapers.repec.org/RePEc:taf:irapec:v:34:y:2020:i:5:p:650-671
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