Heller, B., Mazumdar, S. orcid.org/0000-0002-0748-7638 and Ciravegna, F. orcid.org/0000-0001-5817-4810 (2018) Large scale, long-term, high granularity measurement of active travel using smartphones apps. In: Proceedings. 12th Conference of the International Sports Engineering Association, 26-29 Mar 2018, Brisbane, Australia. MDPI
Abstract
Accurate, long-term data are needed in order to determine trends in active travel, to examine the effectiveness of any interventions and to quantify the health, social and economic consequences of active travel. However, most studies of individual travel behaviour have either used self-report (which is limited in detail and open to bias), or provided logging devices for short periods, so lack the ability to monitor long-term trends. We have developed apps using participants’ own smartphones (Android or iOS) that monitor and feed-back individual user’s physical activity whilst the phone is carried or worn. The nature, time and location of any physical activity are uploaded to a secure survey and allow researchers to identify large scale behaviour. Pilot data from almost 2000 users have been logged and are reported. This constitutes a natural experiment, collecting long-term physical activity, transport mode and route choice information across a large cross-section of users.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Mobile devices; active travel; physical activity |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Funding Information: | Funder Grant number EUROPEAN COMMISSION - HORIZON 2020 688082 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Nov 2018 12:36 |
Last Modified: | 14 Nov 2018 12:36 |
Published Version: | https://doi.org/10.3390/proceedings2060293 |
Status: | Published |
Publisher: | MDPI |
Refereed: | Yes |
Identification Number: | 10.3390/proceedings2060293 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:138557 |