A novel real-time coalminer localization and tracking system based on self-organized sensor networks

  • Authors:
  • Yang Wang;Liusheng Huang;Wei Yang

  • Affiliations:
  • Department of Computer Science and Technology, USTC, Hefei, Anhui, China and Suzhou High Institute of USTC, Suzhou, Jiangsu, China;Department of Computer Science and Technology, USTC, Hefei, Anhui, China and Suzhou High Institute of USTC, Suzhou, Jiangsu, China;Department of Computer Science and Technology, USTC, Hefei, Anhui, China and Suzhou High Institute of USTC, Suzhou, Jiangsu, China

  • Venue:
  • EURASIP Journal on Wireless Communications and Networking - Special issue on design, implementation, and evaluation of wireless sensor network systems
  • Year:
  • 2010

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Abstract

With the development of information technology, we envision that the key of improving coal mine safety is how to get realtime positions of miners. In this paper, we propose a prototype system for real-time coal miner localization and tracking based on self-organized sensor networks. The system is composed of hardware and software platform. We develop a set of localization hardware devices with the Safety Certificate of Approval for Mining Products include miner node, wired fixed access station, and base with optical port. On the software side, we develop a layered software architecture of node application, server management, and information dissemination and broadcasting. We also develop three key localization technologies: an underground localization algorithm using received signal strength indication- (RSSI-) verifying algorithm to reduce the influence of the severe environment in a coal mine; a robust fault-tolerant localization mechanism to improve the inherent defect of instability of RSSI localization; an accurate localization algorithm based on Monte Carlo localization (MCL) to adapt to the underground tunnel structure. In addition, we conduct an experimental evaluation based on a real prototype implementation using MICA2 motes. The results show that our system is more accurate and more adaptive in general than traditional localization algorithms.