Rapid improvements in communications infrastructure and sophistication of commercial
hand-held devices provide a major new source of information for assessing extreme
situations such as environmental crises. In particular, ad hoc collections of humans can
act as "soft sensors" to augment data collected by traditional sensors in a net-centric
environment (in effect, "crowd-sourcing" observational data). A need exists to
understand how to task such soft sensors, characterize their performance and fuse the data
with traditional data sources. In order to quantitatively study such situations, as well as
study distributed decision-making, we have developed an Extreme Events Laboratory
(EEL) at The Pennsylvania State University. This facility provides a network-centric,
collaborative situation assessment and decision-making capability by supporting
experiments involving human observers, distributed decision making and cognition, and
crisis management. The EEL spans the information chain from energy detection via
sensors, human observations, signal and image processing, pattern recognition, statistical
estimation, multi-sensor data fusion, visualization and analytics, and modeling and
simulation. The EEL command center combines COTS and custom collaboration tools in
innovative ways, providing capabilities such as geo-spatial visualization and dynamic
mash-ups of multiple data sources. This paper describes the EEL and several on-going
human-in-the-loop experiments aimed at understanding the new collective observation
and analysis landscape.
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