Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1301
Full metadata record
DC FieldValueLanguage
dc.contributor.authorHettigoda, S-
dc.contributor.authorJayaminda, C-
dc.contributor.authorAmarathunga, U-
dc.contributor.authorThaha, S-
dc.contributor.authorWijesundara, M-
dc.contributor.authorWijekoon, J-
dc.date.accessioned2022-02-21T05:26:34Z-
dc.date.available2022-02-21T05:26:34Z-
dc.date.issued2020-12-10-
dc.identifier.citationS. 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.en_US
dc.identifier.isbn978-1-7281-8412-8-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1301-
dc.description.abstractSecuring 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.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2020 2nd International Conference on Advancements in Computing (ICAC);Vol 1 Pages 488-493-
dc.subjectGeophone Baseden_US
dc.subjectSurveillance Systemen_US
dc.subjectNeural Networksen_US
dc.subjectIoTen_US
dc.titleA Geophone Based Surveillance System Using Neural Networks and IoTen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICAC51239.2020.9357257en_US
Appears in Collections:Department of Computer Systems Engineering-Scopes
Research Papers - Dept of Computer Systems Engineering
Research Papers - IEEE
Research Papers - SLIIT Staff Publications

Files in This Item:
File Description SizeFormat 
A_Geophone_Based_Surveillance_System_Using_Neural_Networks_and_IoT.pdf
  Until 2050-12-31
509.44 kBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.