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Towards a Comprehensive Temporal Classification of Footfall Patterns in the Cities of Great Britain (Short Paper)

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Abstract

The temporal fluctuations of footfall in the urban areas have long been a neglected research problem, and this mainly has to do with the past technological limitations and inability to consistently collect large volumes of data at fine intra-day temporal resolutions. This paper makes use of the extensive set of footfall measurements acquired by the Wi-Fi sensors installed in the retail units across the British town centres, shopping centres and retail parks. We present the methodology for classifying the diurnal temporal signatures of human activity at the urban microsite locations and identify characteristic profiles which make them distinctive regarding when people visit them. We conclude that there exist significant differences regarding the time when different locations are the busiest during the day, and this undoubtedly has a substantial impact on how retailers should plan where and how their businesses operate.

BibTeX - Entry

@InProceedings{lugomer_et_al:LIPIcs:2018:9371,
  author =	{Karlo Lugomer and Paul Longley},
  title =	{{Towards a Comprehensive Temporal Classification of Footfall Patterns in the Cities of Great Britain (Short Paper)}},
  booktitle =	{10th International Conference on Geographic Information  Science (GIScience 2018)},
  pages =	{43:1--43:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Stephan Winter and Amy Griffin and Monika Sester},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2018/9371},
  URN =		{urn:nbn:de:0030-drops-93718},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.43},
  annote =	{Keywords: temporal classification, temporal profiles, time series cluster analysis, Wi-Fi sensors, retail analytics}
}

Keywords: temporal classification, temporal profiles, time series cluster analysis, Wi-Fi sensors, retail analytics
Seminar: 10th International Conference on Geographic Information Science (GIScience 2018)
Issue date: 2018
Date of publication: 2018


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