Department of Computer Science and Engineering, Lehigh University, Bethlehem, PA 18015, USA.
Sensors (Basel). 2012 Nov 5;12(11):14862-86. doi: 10.3390/s121114862.
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.
地下环境传感和监测应用，如检测水入侵或滑坡，这些都可能显著改变土壤的物理性质，可以通过一种新的概念，无线信号网络（WSiN）来实现。无线信号网络利用分布式地下传感器节点的无线信号强度变化来监测和描述被感知区域。为了对地下环境进行事件检测和分类，本文提供了一份详细的土壤特性列表和实验数据，说明无线传播在地下通信环境中是如何受到土壤特性影响的。实验表明，经过校准的无线信号强度变化可以作为感知地下环境变化的指标。利用实际的地下传感器节点，评估了 WSiN 用于地下事件检测的概念，例如检测水入侵、相对密度变化和相对运动。为了使用测量的信号强度作为地下事件的主要指标来对地质事件进行分类，我们提出了一种基于贝叶斯决策理论的基于窗口的最小距离分类器。基于窗口的无线信号网络分类器有两个步骤：事件检测和事件分类。在事件检测中，基于窗口的分类器对称为分类窗口的事件发生区域的地质事件进行分类。提出了一种基于无线信号网络的基于窗口的分类方法，并在实验室实验中进行了漏水实验来评估该方法。在这些实验中，基于无线信号网络的检测和分类方法可以检测和分类地下事件。
