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dc.contributor.authorNaseer, Sabri
dc.contributor.authorM. S., Salim
dc.contributor.authorSarah, Fouad
dc.contributor.authorSyed Alwee Aljunid, Syed Junid
dc.contributor.authorFahad Taha, AL-Dhief
dc.contributor.authorMohd Rashidi, Che Beson
dc.date.accessioned2020-12-31T05:04:49Z
dc.date.available2020-12-31T05:04:49Z
dc.date.issued2018
dc.identifier.citationMATEC Web of Conferences, vol.150, 2018, 6 pagesen_US
dc.identifier.issn2261-236X (online)
dc.identifier.urihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/69206
dc.descriptionLink to publisher's homepage at https://www.matec-conferences.org/en_US
dc.description.abstractRemote and scattered valuable and sensitive locations such as labs and offices inside university campus need efficient monitoring and warning system. As well as scattered area and belonging. This research presents a Real-Time intruder Surveillance System based on a single board computer (SBC). Thus the design and development of a cost effective surveillance management system based SBC that can be deployed efficiently in remote and scattered locations such as universities belonging. The fusion of embedded Python codes with SBC that attached to cameras, Long distance sensors, alerting circuitry and wireless module presents a novel integration based effective cost solution and enhances SBC of much flexibility of improvement and development for pervasive remote locations. The system proves the high integrity of smooth working with web application, it’s cost effective and thus can be deployed as many of units to seize and concisely covered remote and scattered area as well as university belonging and departments. The system can be administrated by a remote user sparsely or geographically away from any networked workstation. The proposed solution offers efficient stand alone, flexibility to upgrade and cheap development and installation as well as cost effective ubiquitous surveillance solution. In conclusion, the system acceptable boundaries of successful intruder recognition and warning alert are computed between 1m and 3m distance of intruder from system camera. Recognition rate of 95% and 83% are achieved and the successful warning alert were in the range of 86-97%.en_US
dc.language.isoenen_US
dc.publisherEDP Sciencesen_US
dc.relation.ispartofseriesMalaysia Technical Universities Conference on Engineering and Technology (MUCET 2017);
dc.subjectSmart Intruder Surveillance Systemen_US
dc.titleDesign and Implementation of an Embedded Smart Intruder Surveillance Systemen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1051/matecconf/201815006019
dc.contributor.urlnaseersabri@yahoo.comen_US


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