Abstract
Organisers of events attracting many people have the important task to ensure the safety of the crowd on their venue premises. Measuring the size of the crowd is a critical first step, but often challenging because of occlusions, noise and the dynamics of the crowd. We have been working on a passive Radio Frequency (RF) sensing technique for crowd size estimation, and we now present three datasets of measurements collected at the Tomorrowland music festival in environments containing thousands of people. All datasets have reference data, either based on payment transactions or an access control system, and we provide an example analysis script. We hope that future analyses can lead to an added value for crowd safety experts.
Highlights
We have been working on a passive Radio Frequency (RF) sensing technique for crowd size estimation, and we present three datasets of measurements collected at the Tomorrowland music festival in environments containing thousands of people
We investigate a relatively young approach to crowd counting: crowd estimations using Radio Frequency (RF) signal features
The use of RF signal features is based on the physical effects of a crowd on RF signals
Summary
Organisers of mass gatherings are tasked with the difficult job of ensuring the safety of crowds on their venue premises. Since 2016, our research team has deployed WSNs at multiple stage environments and editions of the Tomorrowland festival At these deployments, we collected data from RF sensor networks with the aim of finding a correlation between the number of people in an environment and the impacted radio signals within our network. We have yet to do a formal investigation on the trade-off between the number of devices per surface area, the periodicity of the communication cycles and the accuracy of estimated crowd counts Results from such future research would allow us to have a view on viable low-power configurations for future semipermanent deployments. To the best of our knowledge, we are the first to have collected passive RF-based network measurements on crowds of thousands of people In this data descriptor, we make three of the datasets used in our studies publicly available. We aim to provide researchers in the field of crowd counting and crowd modelling with real-life measurements of relatively large crowds in the hopes that future analyses can lead to an added value for crowd safety experts
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