Mobile Mapping of Sporting Event Spectators Using Bluetooth Sensors: Tour of Flanders 2011
Accurate spatiotemporal information on crowds is a necessity for a better management in general and for the mitigation of potential security risks. The large numbers of individuals involved and their mobility, however, make generation of this information non-trivial. This paper proposes a novel methodology to estimate and map crowd sizes using mobile Bluetooth sensors and examines to what extent this methodology represents a valuable alternative to existing traditional crowd density estimation methods. The proposed methodology is applied in a unique case study that uses Bluetooth technology fo... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2012 |
Reihe/Periodikum: | Sensors, Vol 12, Iss 10, Pp 14196-14213 (2012) |
Verlag/Hrsg.: |
MDPI AG
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Schlagwörter: | Bluetooth tracking / mobile sensors / mobile mapping / crowd counting / crowd mapping / Chemical technology / TP1-1185 |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-27083141 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://doi.org/10.3390/s121014196 |
Accurate spatiotemporal information on crowds is a necessity for a better management in general and for the mitigation of potential security risks. The large numbers of individuals involved and their mobility, however, make generation of this information non-trivial. This paper proposes a novel methodology to estimate and map crowd sizes using mobile Bluetooth sensors and examines to what extent this methodology represents a valuable alternative to existing traditional crowd density estimation methods. The proposed methodology is applied in a unique case study that uses Bluetooth technology for the mobile mapping of spectators of the Tour of Flanders 2011 road cycling race. The locations of nearly 16,000 cell phones of spectators along the race course were registered and detailed views of the spatiotemporal distribution of the crowd were generated. Comparison with visual head counts from camera footage delivered a detection ratio of 13.0 ± 2.3%, making it possible to estimate the crowd size. To our knowledge, this is the first study that uses mobile Bluetooth sensors to count and map a crowd over space and time.