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Underground coal mine monitoring with wireless sensor networks

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TLDR
The design of a Structure-Aware Self-Adaptive WSN system, SASA, is discussed, able to rapidly detect structure variations caused by underground collapses, and a sound and robust mechanism for efficiently handling queries under instable circumstances is developed.
Abstract
Environment monitoring in coal mines is an important application of wireless sensor networks (WSNs) that has commercial potential. We discuss the design of a Structure-Aware Self-Adaptive WSN system, SASA. By regulating the mesh sensor network deployment and formulating a collaborative mechanism based on a regular beacon strategy, SASA is able to rapidly detect structure variations caused by underground collapses. We further develop a sound and robust mechanism for efficiently handling queries under instable circumstances. A prototype is deployed with 27 mica2 motes in a real coal mine. We present our implementation experiences as well as the experimental results. To better evaluate the scalability and reliability of SASA, we also conduct a large-scale trace-driven simulation based on real data collected from the experiments.

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References
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Wireless sensor networks for habitat monitoring

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Proceedings ArticleDOI

Dynamic fine-grained localization in Ad-Hoc networks of sensors

TL;DR: A novel approach to the localization of sensors in an ad-hoc network that enables sensor nodes to discover their locations using a set distributed iterative algorithms is described.
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