DocumentCode
497741
Title
A multi-disciplinary approach to high level fusion in predictive situational awareness
Author
Costa, Paulo Cesar G ; Chang, Kuo-Chu ; Laskey, Kathryn B. ; Carvalho, Rommel N.
Author_Institution
Center of Excellence in C4I, George Mason Univ., Fairfax, VA, USA
fYear
2009
fDate
6-9 July 2009
Firstpage
248
Lastpage
255
Abstract
The change of focus in modern warfare from individual platforms to the network has caused a concomitant shift in supporting concepts and technologies. Greater emphasis is placed on interoperability and composeability. New technologies such as SOA and semantically aware systems have come into the spotlight. This paper argues that just as the problem space demands interoperability of diverse technologies, so must the solution space. In other words, not only are new approaches needed, but they must also come together as a seamlessly interoperable technological tool set. This can be accomplished only via a consistent multi-disciplinary approach. In this paper, we present some of the major requirements of today´s predictive situation awareness systems (PSAW), propose our approach as a coordinated mix between state-of-the-art research efforts, and present the architecture for enabling our approach.
Keywords
inference mechanisms; open systems; sensor fusion; composeability; high level fusion; interoperability; multi-disciplinary approach; predictive situational awareness; semantically aware systems; Bayesian methods; Information processing; Intelligent sensors; Ontologies; Semiconductor optical amplifiers; Sensor arrays; Space technology; Uncertainty; Weapons; Web services; Bayesian networks; MEBN; PR-OWL; distributed hybrid inference; naval predictive situational awareness; probabilistic ontologies; probabilistic reasoning; spatio-temporal hybrid analysis; web services;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Fusion, 2009. FUSION '09. 12th International Conference on
Conference_Location
Seattle, WA
Print_ISBN
978-0-9824-4380-4
Type
conf
Filename
5203835
Link To Document