Smart safety early warning system of coal mine production based on WSNs
•A smart safety early warning system based on improved DV-Hop localization algorithm for WSNs.•Choosing anchor nodes and calculating per-hop distance are different from the original DV-Hop.•Using role-reversing weighted distance correction strategy to upgrade the positioning accuracy.•Using multi-eq...
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Veröffentlicht in: | Safety science 2020-04, Vol.124, p.104609, Article 104609 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •A smart safety early warning system based on improved DV-Hop localization algorithm for WSNs.•Choosing anchor nodes and calculating per-hop distance are different from the original DV-Hop.•Using role-reversing weighted distance correction strategy to upgrade the positioning accuracy.•Using multi-equation selection strategy and centroid location algorithm to reduce locating error.
Safety is the primary consideration of underground operation. At present, many large mineral countries are committed to using wireless sensors to reduce the accident rate and prevent casualties and major economic losses through early warning. The existing monitoring and early warning system of wired coal mine can only be used in the main tunnel, while the complex underground working area is still the “blind area” of monitoring and early warning. This paper proposes a smart safety monitoring system based on improved DV-Hop localization algorithm for randomly deployed wireless sensor networks (WSNs), which can position accurate personal tracking in industrial fields, such as mines, underground operations, tunnel engineering, and underground engineering. By choosing anchor nodes and calculating the average per-hop distance between anchor nodes are considerably different from the original DV-Hop. Based on the improved DV-Hop positioning algorithm, the critical safety data related to underground coal mining and associated with the location of the staff can be extracted precisely and analyzed quickly. The simulations show that the enhanced algorithms are able to effectively improve localization accuracy for randomly distributed sensor networks and ensure its safety in complex environment and improve the level of safety production. |
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ISSN: | 0925-7535 1879-1042 |
DOI: | 10.1016/j.ssci.2020.104609 |