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Large-Scale Dataset for Radio Frequency-Based Device-Free Crowd Estimation

IDLab—Faculty of Applied Engineering, University of Antwerp—imec, Sint-Pietersvliet 7, 2000 Antwerp, Belgium
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Received: 14 May 2020 / Revised: 3 June 2020 / Accepted: 6 June 2020 / Published: 9 June 2020
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. View Full-Text
Keywords: crowd estimation; crowd counting; RSSI; wireless sensor network; DASH7 crowd estimation; crowd counting; RSSI; wireless sensor network; DASH7
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Kaya, A.; Denis, S.; Bellekens, B.; Weyn, M.; Berkvens, R. Large-Scale Dataset for Radio Frequency-Based Device-Free Crowd Estimation. Data 2020, 5, 52.

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