Title: A smart urban flood control and warning system based on big data

Authors: Guanlin Chen; Zhikang Zhou; Rongxin Zheng; Tongjun Qi

Addresses: School of Computer and Computing Science, Zhejiang University City College, Hangzhou, 310015, China and College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China ' School of Computer and Computing Science, Zhejiang University City College, Hangzhou, 310015, China ' Hangzhou Municipal Bureau of Data Resources Management, Hangzhou, 310016, China ' Hangzhou Municipal Bureau of Data Resources Management, Hangzhou, 310016, China

Abstract: With the great-leap-forward development of social economy in recent years, urban-scale has expanded rapidly and the problem of urban flood control has become more prominent. The normal flood control system has been unable to meet the requirement of rapid urban development. As the urban drainage facilities improve and the internet of things monitoring equipment increase, the big data era has come. Therefore, a smart urban flood control and warning system based on big data will be crucial. In this paper, a system named smart urban flood control and warning system (SUFCWS) based on big data is proposed. The system is composed of user login, flood control basic data entry, water level and rainfall data search, real-time display, statistical analysis and flood warning, which integrates J2EE platform, SSH2 (Spring+Struts2+Hibernate) framework, the bootstrap front-end development kit, highcharts graphics library and Baidu Maps API. Using GM(1, 1) algorithm of grey forecasting model and back propagation neural network algorithm, SUFCWS can give available early warning of potential urban flood.

Keywords: big data; flood control and warning system; J2EE; neural network; JavaScript.

DOI: 10.1504/IJSN.2018.095144

International Journal of Security and Networks, 2018 Vol.13 No.4, pp.236 - 244

Received: 25 Jan 2018
Accepted: 25 Jan 2018

Published online: 31 Aug 2018 *

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