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Information Technology for Communities: Development of a Web-based 3-D Visualization and Cluster Computing System for Disaster Management
Author(s) -
Ge Jin,
G. Dekker,
John Moreland,
Barbara Nicolai
Publication year - 2020
Publication title -
papers on engineering education repository (american society for engineering education)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--20641
Subject(s) - computer science , visualization , emergency management , geographic information system , process (computing) , computer security , world wide web , operating system , geography , data mining , remote sensing , political science , law
Natural disasters can cause huge loss of life and enormous property damage to local communities. Although it is impossible to avoid the natural disasters, human suffering can be reduced by adopting information technologies to the disaster response missions. In this paper, a Web-based 3-D visualization and cluster computing system was developed to facilitate and expedite the resource distribution process during a disaster. Our disaster management system utilizes state-of-the-art computing cluster with 16 nodes of Intel Xeon-E5 processors (16 cores per node) to process the emergency supply requests from the disaster victims and calculate the optimal resource distribution routes, while considering damaged transportation infrastructures. The optimized resource distribution problem was solved with distributed all-pair shortest path algorithm and the vehicle routing algorithm. The Web-based 3-D visualization system was developed with the Google Earth engine to display the disaster areas, affected households, and resource distribution routes. The computation result from the cluster was automatically uploaded to the Web-based 3-D visualization system, enabling users to immediately see the optimal resource distribution routes in a virtual 3-D environment. The visualization system is flexible and can be easily adapted to a Google earth enabled mobile devices, desktop monitors as well as a cave automatic virtual environment (CAVE). Historical disaster data from the Northwest Indiana was used to demonstrate the functionalities of the developed system.

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