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Article

Distributed and Communication-Efficient Spatial Auto-Correlation Subsurface Imaging in Sensor Networks

Center for Cyber-Physical Systems, University of Georgia, Athens, GA 30602, USA
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Sensors 2019, 19(11), 2427; https://doi.org/10.3390/s19112427
Received: 11 March 2019 / Revised: 30 April 2019 / Accepted: 24 May 2019 / Published: 28 May 2019
(This article belongs to the Section Internet of Things)
A wireless seismic network can be effectively used as a tool for subsurface monitoring and imaging. By recording and analyzing ambient noise, a seismic network can image underground infrastructures and provide velocity variation information of the subsurface that can help to detect anomalies. By studying the variation in the noise cross-correlation function of the noise, it is possible to determine the subsurface seismic velocity and image underground infrastructures. Ambient noise imaging can be done in a decentralized fashion using Distributed Spatial Auto-Correlation (dSPAC). In dSPAC over sensor networks, the cross-correlation is the most intensive communication process since nodes need to communicate their data with neighbor nodes. In this paper, a new communication-reduced method for cross-correlation is presented to meet bandwidth and cost of communication constraints in networks while ambient noise imaging is performed using dSPAC method. By applying the proposed communication-reduced method, we show that energy and computational cost of the nodes is also preserved. View Full-Text
Keywords: sensor networks; communication-reduced; subsurface imaging; cross-correlation; spatial autocorrelation; ambient noise sensor networks; communication-reduced; subsurface imaging; cross-correlation; spatial autocorrelation; ambient noise
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MDPI and ACS Style

Valero, M.; Li, F.; Clemente, J.; Song, W. Distributed and Communication-Efficient Spatial Auto-Correlation Subsurface Imaging in Sensor Networks. Sensors 2019, 19, 2427. https://doi.org/10.3390/s19112427

AMA Style

Valero M, Li F, Clemente J, Song W. Distributed and Communication-Efficient Spatial Auto-Correlation Subsurface Imaging in Sensor Networks. Sensors. 2019; 19(11):2427. https://doi.org/10.3390/s19112427

Chicago/Turabian Style

Valero, Maria, Fangyu Li, Jose Clemente, and Wenzhan Song. 2019. "Distributed and Communication-Efficient Spatial Auto-Correlation Subsurface Imaging in Sensor Networks" Sensors 19, no. 11: 2427. https://doi.org/10.3390/s19112427

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