Pedestrian characterisation in urban environments combining WiFi and AI

Knowing how many people there are in a given scenario offers new possibilities for the development of intelligent services. With this goal in mind, the use of sensors and Radio Frequency (RF) is becoming an interesting alternative to other classic methods such as image processing for counting people. In this paper we present a novel method for counting, characterizing, and localizing pedestrians in outdoor environments, called iPCW (intelligent Pedestrian Characterization using WiFi). iPCW is a passive, device-based sensor system that incorporates artificial intelligence techniques, more specifically, machine techniques. Performance evaluation using intensive computer simulations shows that iPCW excellent results, with moving and static pedestrian detection accuracy above 98% and positioning above 92%.