• Title/Summary/Keyword: TR Module

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Development of an Integrated Forecasting and Warning System for Abrupt Natural Disaster using rainfall prediction data and Ubiquitous Sensor Network(USN) (농촌지역 돌발재해 피해 경감을 위한 USN기반 통합예경보시스템 (ANSIM)의 개발)

  • Bae, Seung-Jong;Bae, Won-Gil;Bae, Yeon-Joung;Kim, Seong-Pil;Kim, Soo-Jin;Seo, Il-Hwan;Seo, Seung-Won
    • Journal of Korean Society of Rural Planning
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    • v.21 no.3
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    • pp.171-179
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    • 2015
  • The objectives of this research have been focussed on 1) developing prediction techniques for the flash flood and landslide based on rainfall prediction data in agricultural area and 2) developing an integrated forecasting system for the abrupt disasters using USN based real-time disaster sensing techniques. This study contains following steps to achieve the objective; 1) selecting rainfall prediction data, 2) constructing prediction techniques for flash flood and landslide, 3) developing USN and communication network protocol for detecting the abrupt disaster suitable for rural area, & 4) developing mobile application and SMS based early warning service system for local resident and tourist. Local prediction model (LDAPS, UM1.5km) supported by Korean meteorological administration was used for the rainfall prediction by considering spatial and temporal resolution. NRCS TR-20 and infinite slope stability analysis model were used to predict flash flood and landslide. There are limitations in terms of communication distance and cost using Zigbee and CDMA which have been used for existing disaster sensors. Rural suitable sensor-network module for water level and tilting gauge and gateway based on proprietary RF network were developed by consideration of low-cost, low-power, and long-distance for communication suitable for rural condition. SMS & mobile application forecasting & alarming system for local resident and tourist was set up for minimizing damage on the critical regions for abrupt disaster. The developed H/W & S/W for integrated abrupt disaster forecasting & alarming system was verified by field application.