클라우드 및 빅데이터 기반 침수 도로 탐색 시스템 개발

Abstract

Recently, although Korea having a distinct temperate seasonal climate natural disasters are increasing rapidly while extreme weather with the unstable weather events and subtropical characteristics such as heavy snow, earthquakes, hurricanes, occurs in urban and mountainous areas. Especially, local torrential rainfalls causes a flood of new types and results in a number of problems such as capital loss or injury to persons. In the present situation, the discussion with regard to disaster alerting and recovery systems for urban disaster has been made in several studies. In this paper, we conducted a study to develop roads flooded area flooding search system utilizing big data when flooding encountered. The data that needs to search for the road flooded area can be defined as a big data update even hundreds of thousands per day. When the emergency situation, road flooded area search system uses a distributed processing platform for rapid processing of big data. Big data collected in this study is social media data such as news, blogs and SNS, weather data provided by the National Weather Service, and the road link data. And database storing each data from the past to present in real time is analyzed by the distributed processing platform in order to searching road flooded area and extracted road flooded areas are given the degree of risk. Distributed processing platform is present in the cloud computing and extracted road flooded area can be provided to the client to obtain information about the actual road flooded area.