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Research on positioning method of industrial wireless sensor networks
oleh: Qingjun Yang, Dongsheng Ji, Yukai Yao, Enzhan Zhang, Xiaoyun Chen
Format: | Article |
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Diterbitkan: | SpringerOpen 2018-10-01 |
Deskripsi
Abstract Location data associated with wireless sensor networks represents critical information. Current developments in localization algorithms employed in industrial wireless sensor networks seek to adopt positioning methods that are more robust and stable, and more accurate and efficient while requiring a minimum of resources. Therefore, the present study capitalizes on the industrial wireless sensor network that has a strong correlation between applications to propose a positioning method design based on a Monte Carlo localization algorithm that is ideally suited to the narrow channel environment encountered in underground mining activities. The proposed positioning method offers very low computational complexity, which greatly reduces the use of network resources. Simulation experiments demonstrate that the proposed Monte Carlo localization algorithm provides strong stability and relatively high positioning accuracy.