iCrowd — A framework for monitoring of identifiable crowd

TLDR: This paper proposes an identifiable crowd monitoring framework named iCrowd, which collect, identify, infer, analyze, store and retrieve the real-time location information of each of the pre-registered participants (pilgrims), and provides a digital view of crowd in near real- time.

Abstract: To manage large crowded events is a very challenging task nowadays. People are looking for solutions in which they can easily monitor the crowd, trace individuals, study formation and deformation patterns of the crowd. Millions of Muslims from around the world gather and perform Hajj in Makkah, Saudi Arabia in the 12th month of every lunar year. To monitor the crowd during Hajj is a great challenge. In this paper, we are proposing an identifiable crowd monitoring framework named iCrowd. This framework collect, identify, infer, analyze, store and retrieve the real-time location information of each of the pre-registered participants (pilgrims), and provides a digital view of crowd in near real-time. iCrowd framework is designed on a three-layer approach, device layer, middleware layer, and the application layer. We demonstrate our proposed framework with simulated data in the context of the event of Hajj.