• Login
    View Item 
    •   DSpace Home
    • Researchers
    • Naseer Sabri Salim
    • View Item
    •   DSpace Home
    • Researchers
    • Naseer Sabri Salim
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Design and Implementation of an Embedded Smart Intruder Surveillance System

    Thumbnail
    View/Open
    Main article (681.2Kb)
    Date
    2018
    Author
    Naseer, Sabri
    M. S., Salim
    Sarah, Fouad
    Syed Alwee Aljunid, Syed Junid
    Fahad Taha, AL-Dhief
    Mohd Rashidi, Che Beson
    Metadata
    Show full item record
    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%.
    URI
    http://dspace.unimap.edu.my:80/xmlui/handle/123456789/69206
    Collections
    • Naseer Sabri Salim [11]
    • Syed Alwee Aljunid Syed Junid, Prof. Ir. Ts. Dr. [123]
    • Mohd Rashidi Che Beson, Ir. Dr. [19]

    Atmire NV

    Perpustakaan Tuanku Syed Faizuddin Putra (PTSFP) | Send Feedback
     

     

    Browse

    All of UniMAP Library Digital RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    Atmire NV

    Perpustakaan Tuanku Syed Faizuddin Putra (PTSFP) | Send Feedback