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Innovative Seismo-Acoustic Applications to Forensics and Novel Monitoring Problems [Poster]

Seismic and acoustic sensors are capable of recording ground motion and acoustic waves originating from many phenomena and activities. Besides traditional monitoring of natural environmental phenomena and military activities, seismo-acoustic measurements can also be used to detect, identify, locate, characterize and monitor animal, domestic and industrial processes that generate recordable acoustic, infrasonic and/or seismic waves. Both established and more innovative data analyses can extract useful information from these wavefields. As our homes, factories and communities get smarter, more data is needed, if not required, for safe operation. The information extracted from seismo-acoustic measurements of both persistent and transient activity will improve our state-of-health assessments of these environments. For example, seismo-acoustic signals related to machinery operations can be used to monitor status and specifics of the machinery independently.

We welcome submissions on collection and analysis of seismo-acoustic data and techniques including but not limited to (1) seismo-acoustic monitoring of animal, domestic and industry activities; (2) acoustic and seismic analyses of chemical, ammunition or vapor explosions; (3) multi-signature fusion of seismo-acoustic data with other geophysical signatures; (4) methods to quantify uncertainties of parameter estimates that are derived from observing surficial, transient sources in noisy and cluttered signal environments; (5) special geophysical considerations of human-made environments that can bias source parameter estimates; (6) leveraging unconventional data streams for association and source location that include social media posts; and (7) machine learning applications to acoustic and seismic signals.

Conveners
Chengping Chai, Oak Ridge National Laboratory (chaic@ornl.gov); Joshua D. Carmichael, Los Alamos National Laboratory (josh.carmichael@gmail.com); Monica Maceira, Oak Ridge National Laboratory (maceiram@ornl.gov); Omar Marcillo, Los Alamos National Laboratory (omarcillo@lanl.gov)

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