12 May 2016 The QuEST for multi-sensor big data ISR situation understanding
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Abstract
The challenges for providing war fighters with the best possible actionable information from diverse sensing modalities using advances in big-data and machine learning are addressed in this paper. We start by presenting intelligence, surveillance, and reconnaissance (ISR) related big-data challenges associated with the Third Offset Strategy. Current approaches to big-data are shown to be limited with respect to reasoning/understanding. We present a discussion of what meaning making and understanding require. We posit that for human-machine collaborative solutions to address the requirements for the strategy a new approach, Qualia Exploitation of Sensor Technology (QuEST), will be required. The requirements for developing a QuEST theory of knowledge are discussed and finally, an engineering approach for achieving situation understanding is presented.
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Steven Rogers, Jared Culbertson, Mark Oxley, H. Scott Clouse, Bernard Abayowa, James Patrick, Erik Blasch, John Trumpfheller, "The QuEST for multi-sensor big data ISR situation understanding", Proc. SPIE 9831, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VII, 98310G (12 May 2016); doi: 10.1117/12.2229722; https://doi.org/10.1117/12.2229722
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