Large scale, long-term, high granularity measurement of active travel using smartphones apps

HELLER, Ben, MAZUMDAR, Suvodeep and CIRAVEGNA, Fabio (2018). Large scale, long-term, high granularity measurement of active travel using smartphones apps. Proceedings, 2 (6), p. 293.

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Official URL: http://www.mdpi.com/2504-3900/2/6/293
Open Access URL: https://www.mdpi.com/2504-3900/2/6/293 (Published)
Link to published version:: https://doi.org/10.3390/proceedings2060293

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.

Item Type: Article
Research Institute, Centre or Group - Does NOT include content added after October 2018: Centre for Sports Engineering Research
Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
Identification Number: https://doi.org/10.3390/proceedings2060293
Page Range: p. 293
Depositing User: Jill Hazard
Date Deposited: 08 Mar 2018 10:29
Last Modified: 08 Apr 2019 10:57
URI: http://shura.shu.ac.uk/id/eprint/18865

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