Information Technology for Communities: Development of a Web-based 3-D Visualization and Cluster Computing System for Disaster Management

Ge Jin; Gerald A. Dekker; John Moreland; Barbara Jean Nicolai

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Conference: 2014 ASEE Annual Conference & Exposition
Location: Indianapolis, Indiana
Publication Date: June 15, 2014
Start Date: June 15, 2014
End Date: June 18, 2014
ISSN: 2153-5965
Conference Session: New Trends in Computing and Information Technology Education
Tagged Division: Computing & Information Technology
Page Count: 12
Page Numbers: 24.749.1 - 24.749.12
DOI: 10.18260/1-2--20641
Permanent URL: https://strategy.asee.org/20641
Download Count: 488

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Paper Authors

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Ge Jin Purdue University Calumet (College of Technology)

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Ge Jin, D.Sc, is currently an assistant professor in the Department of Computer Information Technology and Graphics at the Purdue University Calumet. He teaches computer game development, computer graphics and animation, as well as computer information technology courses at the undergraduate and graduate levels. Prior to joining Purdue University Calumet, he was a postdoctoral research scientist at the George Washington University, Department of Computer Science. Professor Jin holds a B.S. in Computer Science from Peking University, China, and an M.S. in Computer Science from Seoul National University, South Korea. He earned his Doctor of Science degree in Computer Science with a concentration in computer graphics from the George Washington University. His research spans the fields of computer graphics, virtual reality, computer animation, medical visualization, and educational game development. He is a member of the ACM SIGGRAPH, ASEE, and International Society of Virtual Rehabilitation.

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Gerald A. Dekker Jr. Purdue University Calumet

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Gerald Dekker obtained his Master's degree in Computer Science from Purdue University Calumet in 2012. He currently works at the Purdue Calumet Center for Innovation through Visualization and Simulation as a post-graduate researcher in virtual reality and computer graphics.

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John Moreland Purdue University Calumet

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John Moreland is senior research scientist at the Center for Innovation through Visualization and Simulation at Purdue University Calumet. He has MS in Technology, BS in Computer Graphics Technology, and is currently working on a PhD in Technology focusing on the application of mixed reality technologies to education.

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Barbara Jean Nicolai Purdue University Calumet

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Abstract

Information Technology for Communities: Development of a Web-based 3D Visualization and Cluster Computing System for Disaster Management Authors Institution AddressAbstractNatural disasters can cause huge loss of life, enormous amounts of property damage to the localcommunities. Although it is impossible to avoid the natural disasters, human sufferings can bereduced by adopting information technologies to the disaster response missions. In this paper, wedeveloped a web-based 3D visualization and cluster computing system to facilitate and expeditethe resource distribution process during a disaster. FEMA’s Emergency Support Function (ESF) 1presents the guidelines to coordinate transportation request, assess damage to transportationinfrastructures, and provide alternate transportation services. FEMA ESF 6 specifies the guidingprinciples to coordinate the distribution of emergency relief supplies such as shelter, food andemergency first aid to the disaster victims. Our disaster management system utilizes state-of-the-artcomputing cluster with 16 nodes of Intel Xeon-E5 processors (16 cores per node) to process theemergency supply requests from the disaster victims, and calculate the optimal resourcedistribution routes with the consideration of the damaged transportation infrastructures. Theoptimized resource distribution problem was solved with distributed all pair shortest pathalgorithm and the vehicle routing algorithm. The web-based 3D visualization system wasdeveloped with Google earth engine to display the disaster areas, affected households and resourcedistribution routes. The computation result from the cluster was automatically uploaded to theweb-based 3D visualization system, enabling the users to immediately see the optimal resourcedistribution routes in a virtual 3D environment. The visualization system is flexible and can beeasily adapted to a Google earth enabled mobile devices, desktop monitors as well as a Caveautomatic virtual environment (CAVE). A historical disaster data from the Northwest Indianawas used to demonstrate the functionalities of the developed system.

Citation
Format

Jin, G., & Dekker, G. A., & Moreland, J., & Nicolai, B. J. (2014, June), Information Technology for Communities: Development of a Web-based 3-D Visualization and Cluster Computing System for Disaster Management Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. 10.18260/1-2--20641

TY  - CPAPER
AB  -                      Information Technology for Communities:                 Development of a Web-based 3D Visualization and                Cluster Computing System for Disaster Management                                            Authors                                           Institution                                            AddressAbstractNatural disasters can cause huge loss of life, enormous amounts of property damage to the localcommunities. Although it is impossible to avoid the natural disasters, human sufferings can bereduced by adopting information technologies to the disaster response missions. In this paper, wedeveloped a web-based 3D visualization and cluster computing system to facilitate and expeditethe resource distribution process during a disaster. FEMA’s Emergency Support Function (ESF) 1presents the guidelines to coordinate transportation request, assess damage to transportationinfrastructures, and provide alternate transportation services. FEMA ESF 6 specifies the guidingprinciples to coordinate the distribution of emergency relief supplies such as shelter, food andemergency first aid to the disaster victims. Our disaster management system utilizes state-of-the-artcomputing cluster with 16 nodes of Intel Xeon-E5 processors (16 cores per node) to process theemergency supply requests from the disaster victims, and calculate the optimal resourcedistribution routes with the consideration of the damaged transportation infrastructures. Theoptimized resource distribution problem was solved with distributed all pair shortest pathalgorithm and the vehicle routing algorithm. The web-based 3D visualization system wasdeveloped with Google earth engine to display the disaster areas, affected households and resourcedistribution routes. The computation result from the cluster was automatically uploaded to theweb-based 3D visualization system, enabling the users to immediately see the optimal resourcedistribution routes in a virtual 3D environment. The visualization system is flexible and can beeasily adapted to a Google earth enabled mobile devices, desktop monitors as well as a Caveautomatic virtual environment (CAVE). A historical disaster data from the Northwest Indianawas used to demonstrate the functionalities of the developed system.
AU  - Ge Jin
AU  - Gerald A. Dekker Jr.
AU  - John Moreland
AU  - Barbara Jean Nicolai
CY  - Indianapolis, Indiana
DA  - 2014/06/15
PB  - ASEE Conferences
TI  - Information Technology for Communities: Development of a Web-based 3-D Visualization and Cluster Computing System for Disaster Management 
UR  - https://strategy.asee.org/20641
DO  - 10.18260/1-2--20641
ER  -