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For academic researchers

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2022vkarthikvit
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Monitoring physical distancing for crowd management: Real-time trajectory and group analysis Publsnes Gabe 29,2020 + hpses.oVg0.157 sour pene. 0240953 Abstract Physical distancing, as a measure to contain the spreading of Covi-19, is defining @ “new norma". Unless belonging to family, pedestians in sharod spaces are asked to obsorve a minimal (countty-dependent) pairwise distance. Coherenlly, managers of public spaces may be tasked with the enforcement or monitoring ofthis constraint. As privacy-respecful raal-time tracking of pedestrian dynamics in public spaces is a growing really, is natural o leverage on these loals to analyze the adherenca to physical distancing and compare the effeciveness of crowd management measurements. Typical questions are "in which Eonalons nonfamily members infenged social dslancing?", “Are there repeated offenders?" ard "How are new crowd ‘management measures performing?” Notably, dealing wit large crowds, e.g. n tain stations, gets rapidly computationally challenging. n this work we have a two-fold aim: fis, we propose an efficent and scalable analys's framework to process, offine or in realtime, pedestrian tracking data via a sparse graph. The Framework tackles effcienty all he questions mentioned above, Fepresenting pedestian-pedestian teractions via vector-weightad graoh connections. On this basis, we can disentangle csiance offenders and family memoers in a prvacy-complant way, Second, we present a thorough analysis of mutual cistances and ‘exposure-imes ina Dutch tan patfocm, comparing pre-Covid and current dala via physics observables as Radial Distibution Functions, The versatlty anc simplioty of this approach, developes to analyze crowd management measures in public transport facies, enable to tackle issues beyond physical distancing, for instance the prvacy-respeclul detection of groups and the ‘analysis oftheir motion patterns, Citation: Pouw CAS, Toschi F, van Schadewik F, Corbeta A (2020) Monitoring physical dstancing for crowd management: Real-time trajectory and group analysis. PLOS ONE 15(10): €6240863.htps:idoLorg/10.137 journal pone.0240963, Editor: Dante 8. Chialvo, Consejo Nacional de Investigaciones Cientificas y Tecnicas, ARGENTINA, Received: July 30, 2020; Accopted: Augus! 27, 2020; Published: October 28, 2020, ‘Copyright: © 2020 Pouw etal, This 's an open access article dlstibuted under the terms ofthe Creative Commons, D, we memorize (properties of this event within the weight, (6), af he edge © = (py, 22), that connects the two pedestian-nodes py, pa. Specifically, the weight jc) aims ata discrete counterpart of the ROF (g(7, ct. £9.(2)) restricted to pedestrians ps, a2 and with support

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