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Issue title: Special Section: Computational Human Performance Modelling for Human-in-the-Loop Machine Systems
Guest editors: Hoshang Kolivand, Valentina E. Balas, Anand Paul and Varatharajan Ramachandran
Article type: Research Article
Authors: Lianbing, Denga | Daming, Lib; c; * | Zhiming, Caic
Affiliations: [a] Zhuhai Da Hengqin Science and Technology Development Co., Ltd, Hengqin New Area, China | [b] The Post-Doctoral Research Center of Zhuhai Da Hengqin Science and Technology Development Co., Ltd, China | [c] Institute of Data Science, City University of Macau, China
Correspondence: [*] Corresponding author. Li Daming, E-mail: dmli@cityu.mo.
Abstract: In recent years, the problem of urban waterlogging has been highly valued. The application of information technology and image simulation to emergency management of urban waterlogging can improve urban flood prevention and disaster reduction capabilities and reduce disaster losses. In this paper, the author analyze the emergency management system of urban waterlogging based on cloud computing platform and 3D visualization. Collect data through street monitoring and drones, re-analyze the collected images, and screen cities for easy waterlogging. Researchers can rely on the high-performance computing power of the system and the visualized integrated environment to achieve online monitoring and early warning of waterlogging and 3D visual display. The system can provide early warning services in the form of alarms for monitoring results that exceed the threshold, and use mobile agents to send messages to relevant personnel in a variety of ways, providing fast auxiliary decision-making services. The simulation results show that the system has high simulation accuracy and can provide fast and efficient emergency services.
Keywords: Urban Waterlogging, Neural Network, cloud computing, emergency management
DOI: 10.3233/JIFS-189040
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5595-5608, 2020
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