Paper Info
Title
Cloud-based tasking, collection, processing, exploitation, and dissemination
Abstract
The current explosion in sensor data has brought us to a tipping point in the intelligence, surveillance, and reconnaissance technologies. This problem can be addressed through the insertion of novel artificial intelligence-based methodologies. The scope of the problem addressed in this position paper is to propose a novel computational intelligence methodology, which can learn to map distributed heterogeneous data to actionable meaning for dissemination. The impact of this approach is that it will provide a core solution to the tasking, collection, processing, exploitation, and dissemination (TCPED) problem. It will serve to demonstrate the viability of the methodologies core concepts and thus justify a scaled-up investment in its development. Consequently, the expected operational performance improvements include the capture and reuse of analyst expertise, an order of magnitude reduction in required bandwidth, and, for the user, prioritized intelligence based on the knowledge derived from distributed heterogeneous sensing.
Year
DOI
Venue
2013
10.1109/IRI.2013.6642494
Information Reuse and Integration
Keywords
Field
DocType
artificial intelligence,cloud computing,distributed processing,TCPED problem,artificial intelligence based methodologies,cloud computing,computational intelligence methodology,distributed heterogeneous sensing,magnitude reduction,map distributed heterogeneous data,tasking collection processing exploitation and dissemination,Boolean features,Cloud-based tasking,data exploitation,schema instantiation
Artificial architecture,Data mining,Computational intelligence,Reuse,Computer science,Position paper,Operational performance,Bandwidth (signal processing),Artificial intelligence,Machine learning,Cloud computing,Tipping point (climatology)
Conference
Citations 
PageRank 
References 
1
0.37
2
Authors
2
Name
Order
Citations
PageRank
Stuart H. Rubin119931.06
Gordon K. Lee29629.59