Browse > Article
http://dx.doi.org/10.9717/kmms.2015.18.8.925

A Study on the Big Data Analysis System for Searching of the Flooded Road Areas  

Song, Youngmi (Dept. of Information System, Graduate School, Pukyong National University)
Kim, Chang Soo (Dept. of IT Convergence and Application Engineering, Pukyong National University)
Publication Information
Journal of Korea Multimedia Society / v.18, no.8, 2015 , pp. 925-934 More about this Journal
Abstract
The frequency of natural disasters because of global warming is gradually increasing, risks of flooding due to typhoon and torrential rain have also increased. Among these causes, the roads are flooded by suddenly torrential rain, and then vehicle and personal injury are happening. In this respect, because of the possibility that immersion of a road may occur in a second, it is necessary to study the rapid data collection and quick response system. Our research proposes a big data analysis system based on the collected information and a variety of system information collection methods for searching flooded road areas by torrential rains. The data related flooded roads are utilized the SNS data, meteorological data and the road link data, etc. And the big data analysis system is implemented the distributed processing system based on the Hadoop platform.
Keywords
Big Data Analysis; Social Media; Flooded Road Areas; Searching System;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
1 Y.H. Chun, Development of a Decision Support System form Extraction Information and Determination Attributes of Disasters based on Social NetWork, Master’s Thesis of Pukyong National University, 2013.
2 Dalseong Gun Disaster and Safety Countermeasures Headquarters Homepage, http://www.dalseong.daegu.kr/jaehe/sub_menu/accident_public/accident_category.html (accessed Aug. 10, 2014)
3 B.G. Gu, “Hadoop Map/Reduce Implementation Way on GPU Cluster,” Proceedings of KIIT Summer Conference, pp. 49-52, 2012.
4 S. Hur and Y. Kim, “A Design of Analysis System on TV Advertising Effect of Social Networking Using Hadoop,” Journal of Internet Computing and Services, Vol. 14, No. 6, pp. 49-57, 2013.   DOI
5 M. Kim, S. Han, Y. Cui, H. Lee, and C.S. Jeong, “A Hadoop-based Multimedia Transcoding System for Processing Social Media in the PaaS Platform of SMCCSE,” Journal of Korean Sosiety for Internet Information Transaction on Internet and Information Systems, Vol. 6, No. 11, pp. 2827-2848, 2012.
6 Y.I. Cho, “Understanding and major issues of the Big Data,” Journal of Korean Association for Regional Information Society, Vol. 16, No. 3, pp. 43-65, 2013.
7 H.J. Lee, “Application of Big Data Hadoop platform,” The Korean Institute of Communications and Information Sciences, Vol. 29, No. 11, pp. 49-56, 2013.
8 S.W. Seo, J.H. Kim, Y.S. Park, J.S. Lee, and J.S. Myeong, The Hadoop&NoSQL for Mass Data Analysis and Processing, GilBut Publishers, Korea, 2013.
9 Ministry of Security and Public Administration, 2013 Safety Administration White Paper, 11-1312000-000095-10, 2014.
10 E. Kim, H.S. Hwang, and C.S. Kim, “A Study on the Development of the Flood Risk Index for Roads Considering Real-time Rainfall,” Journal of Korea Multimedia Society, Vol. 16, No. 5, pp. 610-618, 2013.   DOI
11 E. Kim, K.H. Rhee, and C.S. Kim, “A Study on the Method of Development of Road Flood Risk Index by Estimation of Real-time Rainfall using the Coefficient of Correlation Weighting Method,” Journal of Korea Multimedia Society, Vol. 17, No. 4, pp. 478-489, 2014.   DOI
12 The National Weather Service Blog, http://kma_131.blog.me/220044187761 (accessed July 20, 2014)
13 T.W. Seo, M.G. Park, and C.S. Kim, “Design and Implementation of the Extraction Mashup for Reported Disaster Information on SNSs,” Journal of Korea Multimedia Society, Vol. 16, No. 11, pp. 1297-1304, 2013. 11.   DOI