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Title
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Large scale crowd density estimation using a sub-GHz wireless sensor network
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Author
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Abstract
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| Automatic crowd density estimation can be very useful for a multitude of applications such as traffic control or crowd control systems during large-scale events. Classic camera-based setups have several shortcomings, the most notorious of which is the privacy issue. The use of a crowd estimator which makes use of a wireless sensor network (WSN) can provide a potential solution to this problem. We deployed a sub-GHz (433 MHz & 868 MHz) wireless sensor network in an indoor stage at a music festival. Visual validation was established by a team of volunteers who manually analyzed a large set of low-quality camera images which were taken during the event. Next, RSS measurements obtained by the network were classified into different density-based categories by a simple probabilistic neural network. Results indicate that the system is capable of estimating the crowd density with a high accuracy, proving the feasibility of using a WSN for such a task. |
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Language
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English
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Source (book)
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29th IEEE Annual International Symposium on Personal, Indoor and Mobile, Radio Communications (PIMRC), September 09-12, 2018, Bologna, Italy
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Publication
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Piscataway, N.J.
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IEEE
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2018
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ISSN
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2166-9589
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ISBN
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978-1-5386-6009-6
978-1-5386-6009-6
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DOI
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10.1109/PIMRC.2018.8580840
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Volume/pages
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(2018)
, p. 849-855
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ISI
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000457761900321
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Full text (Publisher's DOI)
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Full text (publisher's version - intranet only)
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