Title: Smart seismic network for shallow subsurface imaging and infrastructure security

Authors: Maria Valero; Fangyu Li; WenZhan Song

Addresses: Center for Cyber-Physical Systems, University of Georgia, USA ' Center for Cyber-Physical Systems, University of Georgia, USA ' Center for Cyber-Physical Systems, University of Georgia, USA

Abstract: The use of seismic arrays as a tool for imaging subsurface infrastructures and monitoring the corresponding underground activities enables real-time subsurface security and surveillance applications. However, the existing approach relies on manual data collection and centralised computing, which may not work in communication-denied environments. We present a real-time smart seismic imaging system based on ambient noise imaging on networks (ANION) for a variety of subsurface infrastructure imaging applications. The approach integrates in-situ signal processing techniques as well as inter-nodes communication to obtain reliable velocity maps for subsurface characterisation and monitoring. It generates real-time subsurface images by taking advantage of collective computation power in sensor networks while avoiding transferring all raw data to a central place or server. Field tests demonstrate that such a system can detect underground pipelines and potentially its leakage. An exhaustive evaluation regarding bandwidth and communication cost were conducted to highlight the benefits of the proposed approach.

Keywords: smart sensor network; subsurface security; infrastructure detection; activity monitoring; ambient noise.

DOI: 10.1504/IJSNET.2019.101569

International Journal of Sensor Networks, 2019 Vol.31 No.1, pp.10 - 23

Received: 22 May 2019
Accepted: 22 May 2019
Published online: 12 Aug 2019 *

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