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Sensors 2012, 12(11), 14862-14886; doi:10.3390/s121114862

Subsurface Event Detection and Classification Using Wireless Signal Networks

Department of Computer Science and Engineering, Lehigh University, Bethlehem, PA 18015, USA
Department of Civil and Environmental Engineering, Lehigh University, Bethlehem, PA 18015, USA
Author to whom correspondence should be addressed.
Received: 15 August 2012 / Revised: 29 October 2012 / Accepted: 31 October 2012 / Published: 5 November 2012
(This article belongs to the Special Issue Ubiquitous Sensing)


Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events. View Full-Text
Keywords: subsurface sensing; subsurface event detection and classification; Wireless Signal Networks (WSiNs) subsurface sensing; subsurface event detection and classification; Wireless Signal Networks (WSiNs)

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Yoon, S.-U.; Ghazanfari, E.; Cheng, L.; Pamukcu, S.; Suleiman, M.T. Subsurface Event Detection and Classification Using Wireless Signal Networks. Sensors 2012, 12, 14862-14886.

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