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Crowd monitoring technologies are receiving increased attention as they may help mass event organisers preventing disasters in real-time. They mainly aim at forecasting and physically limiting the crowd density at the critical points of the event. In this context, sensors of the crowd density and fluxes on the event are key ingredients. This project aims at conceiving a new passive radar system operating by capturing and processing the signals transmitted by Wi-Fi base stations deployed on mass events to deliver data to the attendees. Groups of attendees will be tracked with the radar and their main features will be estimated. The project will first address the conception of a passive radar based on emerging Wi-Fi communications signals. The radar accuracy gain achieved with the increased signal bandwidth will be explored. Two challenges coming with the Wi-Fi evolution will afterwards be thoroughly investigated: high order modulations that make the reference signal reconstruction more difficult, directive communications that hide part of the radar scene. The project will secondly target the conception of algorithms for identifying and tracking groups of individuals on mass events based on the experimental exploration of their still unknown characteristics. The study will focus on tracking the features that are essential for the crowd monitoring and disaster prevention. In parallel, an experimental setup based on up-to-date software radios will be constructed. The setup will support the design of the radar functionality all along the project based on real-life data acquired on Brussels events.