• DocumentCode
    997176
  • Title

    Surveillance Wireless Sensor Networks: Deployment Quality Analysis

  • Author

    Onur, Ertan ; Ersoy, Cem ; Deliç, Hakan ; Akarun, Lale

  • Author_Institution
    Bogazici Univ., Istanbul, Turkey
  • Volume
    21
  • Issue
    6
  • fYear
    2007
  • Firstpage
    48
  • Lastpage
    53
  • Abstract
    Surveillance wireless sensor networks are deployed at perimeter or border locations to detect unauthorized intrusions. For deterministic deployment of sensors, the quality of deployment can be determined sufficiently by analysis in advance of deployment. However, when random deployment is required, determining the deployment quality becomes challenging. To assess the quality of sensor deployment, appropriate measures can be employed that reveal the weaknesses in the coverage of SWSNs with respect to the success ratio and time for detecting intruders. In this article, probabilistic sensor models are adopted, and the quality of deployment issue is surveyed and analyzed in terms of novel measures. Furthermore, since the presence of obstacles in the surveillance terrain has a negative impact on previously proposed deployment strategies and analysis techniques, we argue in favor of utilizing image segmentation algorithms by imitating the sensing area as a grayscale image referred to as the iso-sensing graph. Finally, the effect of sensor count on detection ratio and time to detect the target is analyzed through OMNeT++ simulation of an SWSN in a border surveillance scenario.
  • Keywords
    image segmentation; probability; surveillance; wireless sensor networks; OMNeT++ simulation; deployment quality analysis; image segmentation; probabilistic sensor model; surveillance wireless sensor network; unauthorized intrusion detection; Aircraft; Costs; Image analysis; Intrusion detection; Monitoring; Personnel; Production facilities; Surveillance; Time measurement; Wireless sensor networks;
  • fLanguage
    English
  • Journal_Title
    Network, IEEE
  • Publisher
    ieee
  • ISSN
    0890-8044
  • Type

    jour

  • DOI
    10.1109/MNET.2007.4395110
  • Filename
    4395110