IDEAS home Printed from https://ideas.repec.org/a/taf/irapec/v34y2020i5p650-671.html
   My bibliography  Save this article

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

Author

Listed:
  • Lorenz Cuno Klopfenstein
  • Saverio Delpriori
  • Paolo Polidori
  • Andrea Sergiacomi
  • Marina Marcozzi
  • Donna Boardman
  • Peter Parfitt
  • Alessandro Bogliolo

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.

Suggested Citation

  • Lorenz Cuno Klopfenstein & Saverio Delpriori & Paolo Polidori & Andrea Sergiacomi & Marina Marcozzi & Donna Boardman & Peter Parfitt & Alessandro Bogliolo, 2020. "Mobile crowdsensing for road sustainability: exploitability of publicly-sourced data," International Review of Applied Economics, Taylor & Francis Journals, vol. 34(5), pages 650-671, September.
    • Handle: RePEc:taf:irapec:v:34:y:2020:i:5:p:650-671
    DOI: 10.1080/02692171.2019.1646223
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02692171.2019.1646223
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02692171.2019.1646223?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:irapec:v:34:y:2020:i:5:p:650-671. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CIRA20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.