Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/69206
Title: Design and Implementation of an Embedded Smart Intruder Surveillance System
Authors: Naseer, Sabri
M. S., Salim
Sarah, Fouad
Syed Alwee Aljunid, Syed Junid
Fahad Taha, AL-Dhief
Mohd Rashidi, Che Beson
naseersabri@yahoo.com
Keywords: Smart Intruder Surveillance System
Issue Date: 2018
Publisher: EDP Sciences
Citation: MATEC Web of Conferences, vol.150, 2018, 6 pages
Series/Report no.: Malaysia Technical Universities Conference on Engineering and Technology (MUCET 2017);
Abstract: Remote 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%.
Description: Link to publisher's homepage at https://www.matec-conferences.org/
URI: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/69206
ISSN: 2261-236X (online)
Appears in Collections:Naseer Sabri Salim
Syed Alwee Aljunid Syed Junid, Prof. Ir. Ts. Dr.
Mohd Rashidi Che Beson, Ir. Dr.

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