Staffordshire University logo
STORE - Staffordshire Online Repository

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

Bolisetti, S., Sharma, M., Patwary, M., SOLIMAN, Abdel-Hamid, Benkhelifa, E. and Maguid, M. (2017) Energy efficient target detection through waveform selection for multi-sensor RF sensing based Internet of Things. Proceedings of the 2017 10th IFIP Wireless and Mobile Networking Conference (WMNC). pp. 1-7. ISSN 2473-3644

[img] Text
Energy Efficient Target Detection Through-Submitted.pdf
Restricted to Repository staff only until 1 September 2019.
Available under License All Rights Reserved.

Download (458kB) | Request a copy

Abstract or description

—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. n 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
Faculty: School of Creative Arts and Engineering > Engineering
Event Title: 10th IFIP Wireless and Mobile Networking Conference (WMNC)
Event Location: Valencia Spain
Event Dates: 25-27 September 2017
Depositing User: Abdel-Hamid SOLIMAN
Date Deposited: 04 Mar 2019 14:41
Last Modified: 04 Mar 2019 14:41
URI: http://eprints.staffs.ac.uk/id/eprint/5424

Actions (login required)

View Item View Item

DisabledGo Staffordshire University is a recognised   Investor in People. Sustain Staffs
Legal | Freedom of Information | Site Map | Job Vacancies
Staffordshire University, College Road, Stoke-on-Trent, Staffordshire ST4 2DE t: +44 (0)1782 294000