Energy efficient target detection through waveform selection for multi-sensor RF sensing based Internet of Things

In this paper, we explore multi-sensor Radio Frequency (RF) sensing based Internet of Things (IoT) for surveillance applications. RF sensing techniques are the next generation technologies which offer distinct advantages over traditional means of sensing. Traditionally, Energy detection (ED) has been used for surveillance applications due to its low computational complexity. However, ED is unreliable due to high false detection rates. There is a need to develop surveillance strategies which offer reliable target detection rates. In this paper, we have proposed a multi-sensor RF sensing based target detection architecture for IoT. To perform surveillance within IoT, multiple sensor nodes are required to co-exist while performing the desired tasks. Interfering waveforms from the neighbouring sensor nodes have a significant impact on the target detection reliability of IoT. In this paper, a waveform selection criterion has been proposed to optimise the target detection reliability and power consumption within IoT in the presence of interfering waveforms.