In brief: Technologies and scientific
methods for real-time seismology are advancing rapidly
at present. In some areas, steady evolution of already
maturing technologies can deliver important improvements
for dynamic risk assessment. In selected areas, new and
emerging technologies in sensors, communication or big
data analysis may have the potential for a
transformative change. RISE prioritises these tasks to
exploit these opportunities:
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Innovative sensors and sensor networks: We will
explore the utility and value of innovative sensor
technologies that offer the potential to increase the
spatial sampling by orders of magnitude. We will
exploit Distributed Acoustic Sensing (DAS) using
dedicated or existing fibre-optics cables, as well as
next generation lower-cost wireless or wired sensors
and hyper-dense networks.
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Promote advances in observational capabilities:
Innovative processing, machine learning and deep
learning approaches have the potential to
revolutionise the way seismic networks operate; they
also demand new approaches to data access and
archiving. Likewise, big-data approaches can be used
to develop dynamic and high-resolution models for
exposure and associated loss.
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Seek earthquake precursors in big-data applications,
such as using ambient noise correlations to
systematically monitor thousands of stations for
changes in seismic wave velocity and attenuation.
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Portable excitation sources for field-testing of
existing and densely instrumented structures.
Lead: University of Edinburgh UEDIN
Participants: ETH Zürich, GFZ, INGV,
IMO, UNIBO, UNINA, EUCENTRE, UGA, BOUN, KNMI, ST-I,
UKRI, QUAKE
Contact:
Prof. Ian Main