There is a need to understand large and complex datasets to provide better situa- tional awareness in-order to make timely well-informed actionable decisions in critical environments. These types of environments include emergency evacuations for large buildings, indoor routing for buildings in emergency situations, large-scale critical infrastructure for disaster planning and first responders, LiDAR analysis for coastal planning in disaster situations, and social media data for health related analysis. I introduce novel work and applications in real-time interactive visual analytics in these domains. I also detail techniques, systems and tools across a range of disciplines from GPU computing for real-time analysis to machine learning for interactive analysis on mobile and web-based platforms.
|Commitee:||Delmelle, Eric, Wang, Xiaoyu, Wartell, Zach|
|School:||The University of North Carolina at Charlotte|
|School Location:||United States -- North Carolina|
|Source:||DAI-B 78/09(E), Dissertation Abstracts International|
|Keywords:||Disaster planning, Interactive visual analytics, Large datasets|
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