A Platform for Overcrowding Detection in Indoor Events Using Scalable Technologies

The increase in the number of large scale events held indoors (i.e. conferences, business events) opens new opportunities for crowd monitoring, access controlling as a way to prevent risks, provide further information about the event's development. In addition, the availability of already connectable devices among attendees allows to perform non-intrusive positioning during the event, without the need of specific tracking devices. We present a platform that integrates the access control management, attendees monitoring based on passive Wi-Fi requests detection,, the analysis, visualization of the captured information using an scalable software architecture. The analysis of the captured information enables to detect crowded zones, the attendance status during the event's performance, after its ending. In addition, the proposed platform has been evaluated using information captured in a real event.