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Bio-Inspired Computing, Information Swarms, and the Problem of Data Fusion

Bio-Inspired Computing

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Technological Innovations in Sensing and Detection of Chemical, Biological, Radiological, Nuclear Threats and Ecological Terrorism

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Abstract

The problem of information overload becomes a huge challenge, particularly when attempting to understanding how to introduce more and more disparate data streams into a data system. Little has been done on how to make those data streams understandable and usable by an analyst. A new paradigm is constructed here, unconstrained by the limits of the current desktop computer, to develop new ways of processing and analyzing data based on the behavior of cellular scale organisms. The additional issue of analytic “groupthink” or “information swarms” is also addressed, with potential solutions to the problem of “paralysis by analysis.”

This paper is the sole responsibility of the author and may not reflect the views of the U.S. Department of State or the U.S. Government.

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Author information

Authors and Affiliations

  1. U.S. Department of State, 2201 C St, NW, Washington, DC, 20520, USA

    Brian Nordmann

Authors
  1. Brian Nordmann
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Correspondence to Brian Nordmann .

Editor information

Editors and Affiliations

  1. , NUARI, Institute for Advanced Sciences Converge, 13873 Park Center Rd, Suite 500, Herndon, 20171, Virginia, USA

    Ashok Vaseashta

  2. Norwich University Applied Research Inst, 158 Harmon Dr., Northfield, 05663, Vermont, USA

    Eric Braman

  3. Norwich University Applied Research Inst, 158 Harmon Dr., Northfield, 05663, Vermont, USA

    Philip Susmann

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Nordmann, B. (2012). Bio-Inspired Computing, Information Swarms, and the Problem of Data Fusion. In: Vaseashta, A., Braman, E., Susmann, P. (eds) Technological Innovations in Sensing and Detection of Chemical, Biological, Radiological, Nuclear Threats and Ecological Terrorism. NATO Science for Peace and Security Series A: Chemistry and Biology. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2488-4_3

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