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SEMINAR: REMINDERr - TODAY - AOML Seminar - 3:00 p.m. - Dr. Milton Halem - "Human Sensor Networks for Extreme Event Mitigation" - \

From: Aoml.Receptionist <aoml.receptionist@noaa.gov>
Subject: SEMINAR: REMINDERr - TODAY - AOML Seminar - 3:00 p.m. - Dr. Milton Halem - "Human Sensor Networks for Extreme Event Mitigation" - \
Date: Thu, 19 Jan 2012 08:18:08 -0500

 AOML Seminar


Date:                Thursday, January 19, 2012


Time:              3:00 p.m. –  - refreshments

                         at 2:45 p.m.   


Location:        AOML First-Floor Conference Room



Speaker:         Dr. Milton Halem 


 Research Professor – Computer Science and     
Electrical Engineering Department – University of Maryland, Baltimore




Title:               "Human Sensor Networks for  Extreme Event Mitigation"


Abstract: Extreme events are phenomena (natural or otherwise) that can have a catastrophic impact on society, such as the loss of human life, destruction of
ecosystems or the creation of wildly chaotic local or global economic changes. Evolving social media of the 21st century and the use of unmanned
auto-piloted mini helicopters and planes with advanced high spectral and spatial resolution instrumentation offer new opportunities for information
technology to respond and help mitigate the impact of natural disasters. We present results of a situation aware human sensor network to improve oil spill
predictive models for the Deep Water Horizon event in the Gulf of Mexico. We propose the use self-organizing maps for determining oil spills from satellite
data and LETKF for data assimilation to estimate flow dependent parameters. We also describe plans to use recent breakthroughs in chaos theory for the computation
of Lagrangian Coherent Structures (a novel mathematical technique that provides profound new insight into transport in complex, time-dependent fluid flows) that can
be used to bound the flow fields. The variety of data types is synthesized in a shared 3-D virtual world visualization tool that can allow many simultaneous users to
undertake several interrelated activities. The technology is based on a distributed decentralized cloud computing service for the pre-processing of data types.
We demonstrate the use of such social media visualization tools for two recent extreme events with substantial socio-economic impact.