Browse > Article
http://dx.doi.org/10.9728/dcs.2018.19.4.771

Design and Implementation of Big Data Analytics Framework for Disaster Risk Assessment  

Chai, Su-seong (Multi-Disaster Countermeasures Organization, Korea Institute of Science and Technology Information)
Jang, Sun Yeon (Mediaflow)
Suh, Dongjun (School of Convergence & Fusion System Engineering, Kyungpook National University)
Publication Information
Journal of Digital Contents Society / v.19, no.4, 2018 , pp. 771-777 More about this Journal
Abstract
This study proposes a big data based risk analysis framework to analyze more comprehensive disaster risk and vulnerability. We introduce a distributed and parallel framework that allows large volumes of data to be processed in a short time by using open-source disaster risk assessment tool. A performance analysis of the proposed system presents that it achieves a more faster processing time than that of the existing system and it will be possible to respond promptly to precise prediction and contribute to providing guideline to disaster countermeasures. Proposed system is able to support accurate risk prediction and mitigate severe damage, therefore will be crucial to giving decision makers or experts to prepare for emergency or disaster situation, and minimizing large scale damage to a region.
Keywords
Disaster Risk Analysis; Distributed & Parallel Framework; Earthquake Damage Estimation; ERGO; Resilience;
Citations & Related Records
연도 인용수 순위
  • Reference
1 M. Joh, "The History and Current Status of the Supercomputers in Institutions for Research and Forecast of Weather/Climate", Atmosphere, Vol. 16, No. 2, pp. 141-157, June 2006.
2 S-W. Kim, G-U. Park, C. Cho, Y-G. Lee, D-B. Yim, "Capability Assessment on Meteorological Technology - Comparative Study of Technological Prowess on Korea, U.S., and Japan", Atmosphere, Vol. 21, No. 3, pp. 319-336, Aug 2011.
3 J. Ahn, C. Park, J. Seo, "A study on the Improvement Plans of Disaster Management Information: Focused on the National Security Management Information System", Journal of Information and Operations Management, Vol. 14, No. 2, pp. 53-76, Seoul National University Institute of Information and Operation Management, Dec 2004.
4 http://www.itfind.or.kr/Report01/200302/IITA/IITA-2230/IITA-2230.pdf
5 W. J. Petak, "Emergency management: A challenge for public administration." Public Administration Review, Vol. 45, pp. 3-7,
6 K. Song, D. Seo, W. Chung M. Seo, "A smart disaster management based on intelligence", Proceedings of the Korean Institute of Communication Sciences Conference, pp. 593-594, Jan 2017.
7 ISO/PAS-22399, "Social Security - Guidelines for incident preparedness and operational continuity management,", International Organization for Standardization, 2007.2007.12.
8 Presto[Internet], Available : https://prestodb.io/
9 Tensorflow[Internet], Available : https://www.tensorflow.org/
10 Keras[Internet], Available : https://keras.io/
11 Datawolf[Internet], Available : https://datawolf.ncsa.illinois.edu/