Energy Efficient Target Detection Through Waveform Selection for Multi-Sensor RF Sensing Based Internet of Things

Bolisetti, S.K. and Sharma, M. and Patwary, Mohammad and Soliman, Abdel-Hamid and Benkhelifa, E. and Maguid, M. (2018) Energy Efficient Target Detection Through Waveform Selection for Multi-Sensor RF Sensing Based Internet of Things. Wireless and Mobile Networking Conference (WMNC), 2017 10th IFIP. ISSN 2473-3644

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Abstract

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.

Item Type:	Article
Identification Number:	10.1109/WMNC.2017.8248856
Dates:	Date Event 1 September 2017 Accepted 8 January 2018 Published Online
Uncontrolled Keywords:	Energy efficiency, internet of things (IoT), multisensor, RF sensing
Subjects:	CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions:	Faculty of Computing, Engineering and the Built Environment Faculty of Computing, Engineering and the Built Environment > College of Computing
Depositing User:	Ian Mcdonald
Date Deposited:	01 Sep 2017 11:19
Last Modified:	22 Mar 2023 12:01
URI:	https://www.open-access.bcu.ac.uk/id/eprint/5116

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