Quadrant-based weighted centroid algorithm for localization in underground mines

Nazish Tahir, Md Monjurul Karim, Kashif Sharif*, Fan Li, Nadeem Ahmed

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

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摘要

Location sensing in wireless sensor networks (WSNs) is a critical problem when it comes to rescue operation in underground mines. Most of the existing research on node localization uses traditional centroid algorithm-based approach. However, such approaches have higher localization error, which leads to inaccurate node precision. This paper proposes a novel quadrant-based solution on weighted centroid algorithm that uses received signal strength indicator for range calculation and distance improvement by incorporating alternating path loss factor according to the mine environment. It also makes use of four beacon nodes instead of traditional three with weights applied to reflect the impact of each node for the centroid position. The weight factor applied is the inverse of the distance estimated. Simulation results show higher localization accuracy and precision as compared to traditional weighted centroid algorithms.

源语言英语
主期刊名Wireless Algorithms, Systems, and Applications - 13th International Conference, WASA 2018, Proceedings
编辑Wei Cheng, Wei Li, Sriram Chellappan
出版商Springer Verlag
462-472
页数11
ISBN(印刷版)9783319942674
DOI
出版状态已出版 - 2018
活动13th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2018 - Tianjin, 中国
期限: 20 6月 201822 6月 2018

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10874 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议13th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2018
国家/地区中国
Tianjin
时期20/06/1822/06/18

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引用此

Tahir, N., Karim, M. M., Sharif, K., Li, F., & Ahmed, N. (2018). Quadrant-based weighted centroid algorithm for localization in underground mines. 在 W. Cheng, W. Li, & S. Chellappan (编辑), Wireless Algorithms, Systems, and Applications - 13th International Conference, WASA 2018, Proceedings (页码 462-472). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 10874 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-94268-1_38