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dc.contributor.authorChidella, Kishore K.
dc.contributor.authorAsaduzzaman, Abu
dc.contributor.authorMashhadi, Farshad
dc.date.accessioned2017-07-16T17:19:18Z
dc.date.available2017-07-16T17:19:18Z
dc.date.issued2017
dc.identifier.citationK. K. Chidella, A. Asaduzzaman and F. Mashhadi, "Prior Detection of Explosives to Defeat Tragic Attacks Using Knowledge Based Sensor Networks," 2017 Ninth Annual IEEE Green Technologies Conference (GreenTech), Denver, CO, 2017, pp. 283-289en_US
dc.identifier.isbn978-1-5090-4535-8
dc.identifier.issn2166-546X
dc.identifier.otherWOS:000404174800043
dc.identifier.urihttp://dx.doi.org/10.1109/GreenTech.2017.47
dc.identifier.urihttp://hdl.handle.net/10057/13479
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractIn recent years, the concern due to targeted acts of terrorism has grown rapidly. The consequences from a terrorist attack lead to critical economic infrastructure, public safety, and environment. Traditional intelligence gathering methods followed by government agencies and physical security systems at vulnerable facilities are not efficient for long-term implications. In this work, we propose a novel self-control solution using knowledge based decision making system (KBDMS) to detect explosives prior to attacks. The proposed system detects explosive materials using sensors, collects invader images (if any) by surveillance cameras, and forwards the information to a base station system (BSS) and/or a monitoring station to alert the emergency services. Adaptive media access control (A-MAC) protocol is used for the communication between the sensors. RSA (Rivest, Shamir and Adleman) algorithm that has digital signatory and integrity of log messages is used to enhance security. The collected information is analyzed at the monitoring station using face recognition techniques, situation reaction techniques, crime and intelligence analysis techniques, and threat severity estimation. The proposed system is evaluated using an Arduino simulator. Experimental results have shown the promise of this approach to defeat tragic attacks by detecting the explosives in prior.en_US
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2017 Ninth Annual IEEE Green Technologies Conference (GreenTech);
dc.subjectA-MAC protocolen_US
dc.subjectExplosive detectionen_US
dc.subjectSensor networksen_US
dc.subjectSurveillance systemsen_US
dc.subjectTerrorist attacksen_US
dc.subjectNational securityen_US
dc.titlePrior detection of explosives to defeat tragic attacks using knowledge based sensor networksen_US
dc.typeConference paperen_US
dc.rights.holderCopyright © 2017, IEEEen_US


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