• DocumentCode
    2631234
  • Title

    Using Ubiquitous Sensor Network to predict the failure of slope by mathematical model

  • Author

    Jung, Hoon ; Kim, Jung-yoon ; Chang, Ki-Tae ; Jung, Chun-Suk

  • Author_Institution
    Electr. Eng., Univ. of Ulsan, Ulsan
  • fYear
    2008
  • fDate
    23-29 June 2008
  • Firstpage
    293
  • Lastpage
    296
  • Abstract
    About 70% of the Korea consists of mountain area, during construction of many roads and railroads cut-slopes are inevitably formed. With the rainy season, frost heaving in winter and thaw in spring can cause the rock falls and landslides in the roads. The failure of the slope is increasing every year with damage of car broken, personal injuries and death of the people. To protect people and property from these damages, we need the real-time monitoring system to detect the early response of slope failures. The GMG applied the TRS sensor units in the slopes to monitor the slope in real-time. But with the data lines, the system is vulnerable with the lightening damage. The whole system can be damaged by one lighting. So we propose the Ubiquitous Sensor Network in this paper. With the USN system we can minimize the lightening damage and can monitor the movement of the slopes consistently.
  • Keywords
    distributed sensors; geomorphology; geophysical equipment; geophysical techniques; monitoring; railways; roads; Korea; Ubiquitous Sensor Network; landslides; mathematical model; mountain area; railroads; real time monitoring system; rock falls; slope failure; Condition monitoring; Geologic measurements; Lightning; Mathematical model; Protection; Real time systems; Roads; Sensor systems; Springs; Terrain factors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Strategic Technologies, 2008. IFOST 2008. Third International Forum on
  • Conference_Location
    Novosibirsk-Tomsk
  • Print_ISBN
    978-1-4244-2319-4
  • Electronic_ISBN
    978-1-4244-2320-0
  • Type

    conf

  • DOI
    10.1109/IFOST.2008.4603023
  • Filename
    4603023