IEEE Radio and Wireless Conference
RAWCON 2004
Banquet Address
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| Banquet
Address
"Distributed
Collaborative Adaptive Sensing for Hazardous Weather
Detection,
Tracking, and Predicting"
Prof. David McLaughlin
University of Massachusetts Amherst
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Abstract:
Our ability to monitor, anticipate, and respond to changing
circumstances and events is increasingly important, particularly
with regard to our physical surroundings. Nowhere is this
capability more vital to society, or the challenges associated
with its practical implementation greater, than in the context
of the atmosphere, where hazardous local weather, such as
thunderstorms, tornadoes, and floods - as well as lofted radiological,
chemical and biological agents - can, in a matter of minutes
or hours, destroy or contaminate life and property over vast
areas. Yet, the portion of the atmosphere that contains the
bulk of both natural and man-made hazards - the lower troposphere
and particularly the atmospheric boundary layer - is grossly
undersampled by today's sensing technologies.
This talk describes a brand new paradigm for atmospheric
sensing -- Distributed Collaborative Adaptive Sensing (DCAS)
- that offers the potential to comprehensively map the wind
field, rainfall rate, and the thermodynamic state of the lower
troposphere, and thus significantly improve our ability to
observe, understand, predict, and warn against atmospheric
hazards. DCAS refers to the use of large numbers of small
solid state radars that are spatially distributed to achieve
high spatial and temporal resolution throughout the entire
troposphere. The radars collaborate with each other via a
distributed computing and communications infrastructure, adapting
to changing atmospheric conditions in a manner that meets
the competing needs of multiple end-users. Installing DCAS
radar networks on cell towers and rooftops defeats the earth
curvature problem that limits today's long-range radar networks
and offers the potential to achieve breakthrough improvements
in sensitivity and resolution compared to current approaches.
These systems promise significant reductions in tornado false-alarms,
vastly improved precipitation estimates for flood prediction,
fine-scale wind field imaging and thermodynamic state estimation
for use in airborne hazard dispersion prediction and other
applications.
The Center for Collaborative Adaptive Sensing of the Atmosphere
(CASA) is a new NSF Engineering Research Center created between
UMASS-Amherst, Colorado State University, the University of
Oklahoma and University of Puerto Rico- Mayaguez. Working
with a consortium of, industrial partners such as Raytheon,
IBM, and Vasiala, and outreach partners at Rice University,
the Texas Medical Center, and the University of Delaware,
this team will seek to create the underlying knowledge and
technology basis for Distributed Collaborative Adaptive Sensing.
A centerpiece of the CASA plan is the systems engineering,
deployment, testing, and operation of field-scale DCAS systems
that will be deployed in tornado alley in Oklahoma, in flood-prone
Houston, TX, and across the Commonwealth of Puerto Rico, where
tropical storms are an all too frequent hazard. This seminar
will describe CASA's vision and technology roadmap and address
our plans for building these systems and for achieving collaboration
among a geographically distributed group of experts from multiple
disciplines.
Biography:
David McLaughlin is a member of the Electrical and Computer
Engineering faculty at UMASS Amherst and Director of the NSF
CASA Engineering Research Center. He received his PhD from
UMASS in 1989, spent the period from 1989 through 1999 at
Northeastern University, and joined the UMASS faculty in January
of 2000, where he holds the Armstrong Professorship in Engineering.
His research interests include radar remote sensing, hurricane
chasing, and sensor networks.
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