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Project

Valorization of a large-scale crowd-density system.

Automatic crowd density estimation can be highly useful for a multitude of applications, examples of which are traffic control, gauging interest at a trade fair and crowd control systems during large-scale events. Classic camera-based setups have several shortcomings, the most notorious of which is the potential for privacyrelated issues to occur. The use of a passive crowd estimator which makes use of an RF-based wireless sensor network (WSN) could provide a solution to this problem. A series of experiments which we performed by installing WSNs in large-scale music festival environments containing thousands of individuals indicated that the influence of the crowd on radio frequency communication within these networks can be used to obtain accurate crowd size estimates. In this project, we seek to validate this core principle for different types and sizes of environments. Furthermore, we wish to investigate how the environment type is related to the network size and the amount of training that is required to obtain accurate results. Finally, an in-depth analysis regarding the crowd density within subregions of these environments and the potential for this approach to allow for crowd flows to be determined, will be investigated as well. Furthermore, to commercialize this proof-of-concept, a go-to-market strategy will be further finetuned. This includes the identification of the different application sectors and to address the different benefits for customers.
Date:1 Nov 2019 →  30 Oct 2020
Keywords:WIRELESS NETWORKS, CROWD DENSITY MONITORING
Disciplines:Embedded and real-time systems, Sensing, estimation and actuating