Edge-based Passive Crowd Monitoring Through WiFi Beacons

Tracking people’s flows has become crucial, not only for safety and security, but also for numerous practical business applications and better management of urban spaces, facilities and services. In this paper, we proposed methodologies that, exploiting IoT technology deployed at the edge of the network, allow for the analysis of people’s movement in urban environments, both outdoors and indoors. In particular, leveraging the use of WiFi probe packets sent by smart devices carried by people on the move, we first describe an implementation of our methodology using off-the-shelf hardware to count people boarding public transportation vehicles. We then present an alternate implementation using commercial WiFi scanners connected to the edge and leveraging suitably deployed virtual network functions to process the data collected by a OneM2M IoT platform, proposing also a mobility tracking procedure that can be applied to anonymized data provided by commercial WiFi scanners. Our experimental results show that the proposed approaches to people counting and mobility detection can achieve a good level of accuracy, while overall carrying a low price tag.