Presentation
Visual Analytics for Real-Time Flight Behavior Threat Assessment
2018 IEEE International Conference on Big Data (Big Data)
(2018)
Abstract
We propose integrating data visualization and machine learning techniques to support Air Traffic Controller (ATC) systems for detecting and identifying friendly/unfriendly aircraft. Our platform composes data-driven decisions to optimize strategic, and operative elements of an ATC system and mitigates its drawbacks by analyzing real-time data from a radar system. A threat assessment approach that incorporates flight behavior assessment, based on visualizing flight data together with flight anomaly prediction and flight origin/destination prediction can be used in cases where the system fails. Furthermore, our proposed integrated tool lets users quickly identify flights and security concerns by analyzing and visualizing data.
Disciplines
Publication Date
December 10, 2018
Location
Seattle, WA, USA
DOI
10.1109/BigData.2018.8622086
Citation Information
Bo Sun, Eric Zielonka, Aleksandr Fritz, Matthew Schofield, et al.. "Visual Analytics for Real-Time Flight Behavior Threat Assessment" 2018 IEEE International Conference on Big Data (Big Data) (2018) Available at: http://works.bepress.com/shen-shyang-ho/8/