Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1301
Title: A Geophone Based Surveillance System Using Neural Networks and IoT
Authors: Hettigoda, S
Jayaminda, C
Amarathunga, U
Thaha, S
Wijesundara, M
Wijekoon, J
Keywords: Geophone Based
Surveillance System
Neural Networks
IoT
Issue Date: 10-Dec-2020
Publisher: IEEE
Citation: S. Hettigoda, C. Jayaminda, U. Amarathunga, S. Thaha, M. Wijesundara and J. Wijekoon, "A Geophone Based Surveillance System Using Neural Networks and IoT," 2020 2nd International Conference on Advancements in Computing (ICAC), 2020, pp. 488-493, doi: 10.1109/ICAC51239.2020.9357257.
Series/Report no.: 2020 2nd International Conference on Advancements in Computing (ICAC);Vol 1 Pages 488-493
Abstract: Securing our assets and properties from intruders and thieves has become increasingly challenging as intruders become technology aware. The most common approach to monitor physical assets is CCTV. However, this approach has a number of technical limitations in addition to the cost. The CCTV camera location is visible to the intruder and intruder can also identify possible blind spots in the CCTV coverage area. In this paper, we introduce a novel method to secure physical assets using Geophones, Neural Networks, and IoT Platforms. This can either be used stand alone or to complement existing CCTV systems. In this approach, the system monitors vibrations on ground to detect intruders. We have achieved up to 93.90% overall accuracy for person identification. The system is invisible to intruders and covers a large area with a smaller number of nodes, thereby reducing the cost of ownership.
URI: http://rda.sliit.lk/handle/123456789/1301
ISBN: 978-1-7281-8412-8
Appears in Collections:Department of Computer Systems Engineering-Scopes
Research Papers - Dept of Computer Systems Engineering
Research Papers - IEEE
Research Papers - SLIIT Staff Publications

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