Abstract
Seismic sensing, a kind of passive sensing technique with high sensitivity and robustness, is a powerful tool to detect moving targets. Distributed seismic sensors can be fully buried under the ground, sensing slight ground deformations induced by moving targets. We name these interconnected seismic acquisition systems the Internet of ground neurons (IoGN). Although the IoGN plays an important role in monitoring key territories and sensitive areas, there are few reviews covering its development and future trends. To fill this gap and inspire further research, we conduct a comprehensive survey on moving target recognition with the IoGN. In this article, we first introduce the architecture and components of the IoGN, as well as hardware systems, including two representative types of seismic sensors and corresponding data acquisition units. Next, we systematically summarize the detection and classification algorithms for target recognition. Detailed case studies of these methods are also reviewed. Finally, we present the current tasks and challenges in IoGN research and provide potential solutions for each challenge.
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