Cloud-Based Tasking, Collection, Processing, Exploitation, and Dissemination in a Case-Based Reasoning System

  • Stuart H. Rubin
  • Gordon K. Lee
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 263)


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 chapter 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. 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. A simple schema example is presented and an instantiation of it shows how to practically create feature search spaces. Given the availability of high-speed parallel processors, such an arrangement allows for the effective conceptualization of non-random causality.


Boolean features Case-based reasoning (CBR) Cloud-based tasking Data exploitation Schema instantiation 



The authors thank SSC-PAC for financial support. This research document was produced, in part, by a U.S. government employee as part of his official duties.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.SSC-PACSan DiegoUSA
  2. 2.Department of Electrical and Computer EngineeringSan Diego State UniversitySan DiegoUSA

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