Large-Scale Crowd Analysis through the Use of Passive Radio Sensing Networks

Clicks: 388
ID: 113428
2020
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Abstract
The creation of an automatic crowd estimation system capable of providing reliable, real-time estimates of human crowd sizes would be an invaluable tool for organizers of large-scale events, particularly so in the context of safety management. We describe a set of experiments in which we installed a passive Radio Frequency (RF) sensor network in different environments containing thousands of human individuals and discuss the accuracy with which the resulting measurements can be used to estimate the sizes of these crowds. Depending on the selected training approach, a median crowd estimation error of 184 people could be obtained for a large scale environment which contained 3227 people at its peak. Additionally, we look into the potential benefits of dividing one of our experimental environments into multiple subregions and open up a potentially interesting new topic of research regarding the estimation of crowd flows. Finally, we investigate the combination of our measurements with another sources of crowd-related data: sales data from drink stands within the environment. In doing so, we aim to integrate the concept of an automatic RF-based crowd estimation system into the broader domain of crowd analysis.
Reference Key
denis2020sensorslarge-scale Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Stijn Denis;Ben Bellekens;Abdil Kaya;Rafael Berkvens;Maarten Weyn;Denis, Stijn;Bellekens, Ben;Kaya, Abdil;Berkvens, Rafael;Weyn, Maarten;
Journal sensors
Year 2020
DOI
10.3390/s20092624
URL
https://www.mdpi.com/1424-8220/20/9/2624#citedby
Keywords
Wireless sensor networks passive sensing wsn radio frequency rf crowd counting device-free sensorless sensing crowd estimation crowd analytics footfall analytics National Center for Biotechnology Information NCBI NLM MEDLINE pubmed abstract nih national institutes of health national library of medicine pmid:32375382 pmc7249162 doi:10.3390/s20092624 stijn denis ben bellekens maarten weyn

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