• DocumentCode
    3482741
  • Title

    Study on IoT based wild vegetation community ecological monitoring system

  • Author

    Nae-Soo Kim ; Kyeseon Lee ; Jae-Hong Ryu

  • Author_Institution
    IoT Convergence Res. Dept., Electron. & Telecommun. Res. Inst., Daejeon, South Korea
  • fYear
    2015
  • fDate
    7-10 July 2015
  • Firstpage
    311
  • Lastpage
    316
  • Abstract
    This paper presents a study on the Internet of Things based low-power wireless sensor networks for remote monitoring of wildlife ecosystem due to climate change. Especially, it is targeting the wild vegetation communities ecological monitoring. First, this paper is presented the platform concept that can effectively monitor, analyze and predict the ecosystem changes based on Internet of Things technology. Based on this, this paper is proposed the required sensors and system architecture of low-power wireless sensor networks based on Internet of Things for the wild vegetation community ecological monitoring. In addition, the design and implementation results for the main components of the system are shown. Finally, it shows the operating results of test-bed which was applied to real wild trees, using the developed prototype.
  • Keywords
    Internet of Things; computerised monitoring; ecology; geophysical techniques; geophysics computing; vegetation; wireless sensor networks; climate change; internet of things based low-power wireless sensor networks; internet of things based wild vegetation community ecological monitoring system; low- power wireless sensor networks; remote monitoring; system architecture; wild trees; Communities; Ecosystems; Logic gates; Monitoring; Sensors; Vegetation mapping; Wireless sensor networks; Ecological Monitoring; Internet of Things; Wild Vegetation Community; Wireless Sensor Network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Ubiquitous and Future Networks (ICUFN), 2015 Seventh International Conference on
  • Conference_Location
    Sapporo
  • ISSN
    2288-0712
  • Type

    conf

  • DOI
    10.1109/ICUFN.2015.7182556
  • Filename
    7182556