WiFi positioning and Big Data to monitor flows of people on a wide scale

Abstract

The possibility to count the accesses to a site and monitor the internal movements of people can be useful in many different scenarios. In this respect, a WiFi network can be exploited to count accesses and estimate users position. This study extends this principle to a wide spatial area and to a large number of users, introducing synergies between Big Data and localization techniques. The 2016 Open Day of the Joint Research Centre (JRC), Ispra (Italy), was a good opportunity to investigate the potential of Big Data and positioning techniques. During the event, which counted the participation of some 8000 people within an area of about 167 hectares, 20 WiFi access points, scattered across the site, recorded the access of wireless devices, such as smartphones and tablets, belonging to visitors and volunteers. By exploiting the Media Access Control (MAC) address (the device unique identifier) through a data-cleaning process, the data analysis allowed estimating the number of participants to the event and the space/time evolution of their position. Moreover, the visitors flow was reconstructed using a Weigthed Centroid (WeC) algorithm. The results achieved, in terms of number of participants, confirmed the data of the JRC registry report compiled at the entrance points of the area. In addition, the results relative to the people flow within the site were found compatible with the scheduling of the event and with its actual progress.