Human cognitive and perceptual factors in JDL level 4 hard/soft data fusion

Jeffrey C. Rimland; David L. Hall; Jacob L. Graham

doi:10.1117/12.919220

10 May 2012 Human cognitive and perceptual factors in JDL level 4 hard/soft data fusion

Jeffrey C. Rimland, David L. Hall, Jacob L. Graham

Proceedings Volume 8407, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012; 84070R (2012) https://doi.org/10.1117/12.919220
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

Utilization of human participants as "soft sensors" is becoming increasingly important for gathering information related to a wide range of phenomena including natural and man-made disasters, environmental changes over time, crime prevention, and other roles of the "citizen scientist." The ubiquity of advanced mobile devices is facilitating the role of humans as "hybrid sensor platforms", allowing them to gather data (e.g. video, still images, GPS coordinates), annotate it based on their intuitive human understanding, and upload it using existing infrastructure and social networks. However, this new paradigm presents many challenges related to source characterization, effective tasking, and utilization of massive quantities of physical sensor, human-based, and hybrid hard/soft data in a manner that facilitates decision making instead of simply amplifying information overload. In the Joint Directors of Laboratories (JDL) data fusion process model, "level 4" fusion is a meta-process that attempts to improve performance of the entire fusion system through effective source utilization. While there are well-defined approaches for tasking and categorizing physical sensors, these methods fall short when attempting to effectively utilize a hybrid group of physical sensors and human observers. While physical sensor characterization can rely on statistical models of performance (e.g. accuracy, reliability, specificity, etc.) under given conditions, "soft" sensors add the additional challenges of characterizing human performance, tasking without inducing bias, and effectively balancing strengths and weaknesses of both human and physical sensors. This paper addresses the challenges of the evolving human-centric fusion paradigm and presents cognitive, perceptual, and other human factors that help to understand, categorize, and augment the roles and capabilities of humans as observers in hybrid systems.

Citation Download Citation

Jeffrey C. Rimland, David L. Hall, and Jacob L. Graham "Human cognitive and perceptual factors in JDL level 4 hard/soft data fusion", Proc. SPIE 8407, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012, 84070R (10 May 2012); https://doi.org/10.1117/12.919220

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