DocumentCode :
2496116
Title :
PROGNOS: Predictive situational awareness with probabilistic ontologies
Author :
Carvalho, R.N. ; Costa, P.C.G. ; Laskey, K.B. ; Chang, K.C.
Author_Institution :
Sensor Fusion Lab., George Mason Univ., Fairfax, VA, USA
fYear :
2010
fDate :
26-29 July 2010
Firstpage :
1
Lastpage :
8
Abstract :
Information in the battlefield comes from reports from diverse sources, in distinct syntax, and with different meanings. There are many kinds of uncertainty involved in this process, e.g., noise in sensors, incorrect, incomplete, or deceptive human intelligence, and others, which makes it essential to have a coherent, consistent, and principled means to represent such phenomena among the systems performing Predictive Situation Awareness (PSAW). PROGNOS is a PSAW system being developed to work within the operational context such as U.S. Navy´s FORCENet. It employs probabilistic ontologies in a distributed system architecture as a means to provide semantic interoperability within an intrinsically complex and uncertain environment. This paper explores our current status in developing the system while addressing the major research challenges for making an effective PSAW system to support maritime operations.
Keywords :
inference mechanisms; marine systems; military computing; ontologies (artificial intelligence); PROGNOS; battlefield; distinct syntax; distributed system architecture; maritime operation; predictive situational awareness; probabilistic ontology; semantic interoperability; Algorithm design and analysis; Bayesian methods; Cognition; Inference algorithms; Marine vehicles; Ontologies; Probabilistic logic; Bayesian networks; MEBN; PROWL; distributed hybrid inference; predictive situational awareness; probabilistic ontologies; probabilistic reasoning; spatio-temporal hybrid analysis; web services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Fusion (FUSION), 2010 13th Conference on
Conference_Location :
Edinburgh
Print_ISBN :
978-0-9824438-1-1
Type :
conf
DOI :
10.1109/ICIF.2010.5711970
Filename :
5711970
Link To Document :
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