Radios as Sensors

Radio receivers, besides acting as wireless network nodes participating to the Internet of Things (IoT) communication task, may act as opportunistic sensors participating to the IoT sensing task. In particular, a radio receiver is intrinsically an electronic sensor which may be used for device-free human activity recognition. In this paper, we analyze recent results on how the identification of the human body presence and movement can be carried out analyzing the RF signals transmitted by sources of opportunity. The impact of channel bandwidth, transmission mode, carrier frequency, and signal descriptors on the recognition performance is discussed. Moreover, we present a novel crowd counting system and assess the performance considering two different types of signal descriptors. Results prove the effectiveness of the presented crowd counting system and allow to get more insights into the relation among the specific sensed environment, chosen signal descriptors, and classification accuracy.