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

Abstract

A WiFi network can be exploited to count accesses and estimate position users. 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 technique was tested during the 2016 JRC Open Day. Exploiting MAC address through a data-cleaning process, the data analysis allowed estimating the number of participants to the event and the time evolution of their position. Visitors flow was reconstructed using a WeC algorithm. The results achieved, confirmed the data of the JRC registry report compiled at the entrance points. In addition, the results relative to the people flow within the site were found compatible with the scheduling of the event.