Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Philip Rutten"'
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-16 (2022)
Abstract Understanding how contact patterns arise from crowd movement is crucial for assessing the spread of infection at mass gathering events. Here we study contact patterns from Wi-Fi mobility data of large sports and entertainment events in the J
Externí odkaz:
https://doaj.org/article/a1f5a6e5aece427cb8a681c0434043b0
Publikováno v:
EPJ Data Science, Vol 10, Iss 1, Pp 1-26 (2021)
Abstract Pedestrian movements during large crowded events naturally consist of different modes of movement behaviour. Despite its importance for understanding crowd dynamics, intermittent movement behaviour is an aspect missing in the existing crowd
Externí odkaz:
https://doaj.org/article/9123b4528a7a4e40af41ab4c00a3dbba
Autor:
Sonja Georgievska, Philip Rutten, Jan Amoraal, Elena Ranguelova, Rena Bakhshi, Ben L. de Vries, Michael Lees, Sander Klous
Publikováno v:
Journal of Big Data, Vol 6, Iss 1, Pp 1-23 (2019)
Abstract We address the problem of detecting highly raised crowd density in situations such as indoor dance events. We propose a new method for estimating crowd density by anonymous, non-participatory, indoor Wi-Fi localization of smart phones. Using
Externí odkaz:
https://doaj.org/article/7d4a8ff6487d4186a6fe00647692909e
Publikováno v:
Physica A: Statistical Mechanics and its Applications, 563:125448. Elsevier
There has been a number of reports showing evidence that human movement behaviour follows patterns resembling Levy walks. These studies focus on the foraging patterns of rural humans and human hunter-gatherers. Here, we investigate motion patterns of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::703aacf6854b35f0b352bde565b1c8a0
https://hdl.handle.net/11245.1/468c9e68-b8ad-4546-b6f3-6a3b6bb08bd2
https://hdl.handle.net/11245.1/468c9e68-b8ad-4546-b6f3-6a3b6bb08bd2
Autor:
Rena Bakhshi, Philip Rutten, Michael Lees, Sonja Georgievska, Sander Klous, Jan Amoraal, Ben L. de Vries, Elena Ranguelova
Publikováno v:
Journal of Big Data, 6:31. Springer Open
Journal of Big Data, Vol 6, Iss 1, Pp 1-23 (2019)
Journal of Big Data, Vol 6, Iss 1, Pp 1-23 (2019)
We address the problem of detecting highly raised crowd density in situations such as indoor dance events.We propose a new method for estimating crowd density by anonymous, non-participatory, indoor Wi-Fi localization of smart phones. Using a probabi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e4447655d05805bb1c319970df42e4fb
https://doi.org/10.1186/s40537-019-0194-3
https://doi.org/10.1186/s40537-019-0194-3