Doyle, John, Hung, Peter, Farrell, Ronan and McLoone, Sean F. (2014) Population Mobility Dynamics Estimated from Mobile Telephony Data. Journal of Urban Technology, 21 (2). pp. 109-132. ISSN 1063-0732
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Abstract
In the last decade, mobile phones and mobile devices using mobile cellular telecommunication
network connections have become ubiquitous. In several developed
countries, the penetration of such devices has surpassed 100 percent. They facilitate communication
and access to large quantities of data without the requirement of a fixed
location or connection. Assuming mobile phones usually are in close proximity with the
user, their cellular activities and locations are indicative of the user’s activities and movements.
As such, those cellular devices may be considered as a large scale distributed human
activity sensing platform. This paper uses mobile operator telephony data to visualize the
regional flows of people across the Republic of Ireland. In addition, the use of modified
Markov chains for the ranking of significant regions of interest to mobile subscribers is
investigated. Methodology is then presented which demonstrates how the ranking of significant
regions of interest may be used to estimate national population, results of which
are found to have strong correlation with census data.
Item Type: | Article |
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Additional Information: | Cite this article as: John Doyle, Peter Hung, Ronan Farrell & Seán McLoone (2014) Population Mobility Dynamics Estimated from Mobile Telephony Data, Journal of Urban Technology, 21:2, 109-132, DOI: 10.1080/10630732.2014.888904. The research presented in this paper was funded by a Strategic Research Cluster grant (07/SRC/I1168) by Science Foundation Ireland under the National Development Plan and by the Irish Research Council under their Embark Initiative in partnership with ESRI Ireland. |
Keywords: | call detail records; imperfect trajectories; Markov chain; stationary distribution; population estimation; |
Academic Unit: | Faculty of Science and Engineering > Electronic Engineering |
Item ID: | 9577 |
Identification Number: | 10.1080/10630732.2014.888904 |
Depositing User: | Ronan Farrell |
Date Deposited: | 20 Jun 2018 16:31 |
Journal or Publication Title: | Journal of Urban Technology |
Publisher: | Taylor & Francis |
Refereed: | Yes |
Funders: | Science Foundation Ireland (SFI), Irish Research Council |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/9577 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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