Subsurface Event Detection and Classification Using Wireless Signal Networks

Abstract

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.

The Role of Advanced Sensing in Smart Cities

“…These allow early detection of earthquakes or landslides, which can be used for early warnings in emergency situations. In [70] a wireless sensor network is suggested to monitor sub-soil activity. Sensor nodes are buried underground.…”

“…Sensor nodes are buried underground. In contrast to other monitoring techniques, which rely on sensors attached to the sensor node, the technique proposed in [70] relies on how the propagation signal is affected by soil conditions. By considering changes in the received signal strength (RSS), it is possible to infer events based on how each soil parameter affects the signal.…”

Toward the Internet of Underground Things: A Systematic Survey

“…Hence, the concept of low frequency (below 500 kHz) was introduced in [16]- [18] to achieve more considerable transmission distance (in tens of meters) for UGWSNs. The received power formula for the EM signals in [16]- [18] is given as…”

“…To investigate the use of EM waves for underground communications, various frequencies of the EM spectrum were examined in the past starting from below 500 kHz [16]- [18] to 120 THz [19]. Depending on the frequency of EM waves, the transmission range of EM signal varies from a few meters (few hundred kHz) to centimeters (THz).…”