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High-accuracy iterative localization algorithm for underground mine WSNs with dynamic path loss optimization and RSSI

Bin Wu1

  • 1Information Engineering School, Chengyi College, Jimei University, Xiamen, China. binwu@stu.xmu.edu.cn.

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|November 20, 2025
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Summary
This summary is machine-generated.

This study introduces an improved localization algorithm for wireless sensor networks (WSNs) in underground mines. It enhances accuracy by optimizing Received Signal Strength Indicator (RSSI) data, improving safety and efficiency.

Keywords:
Dynamic path loss optimizationIterative weighted centroidMine positioningRSSI clusteringWireless sensor networks (WSNs)

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Area of Science:

  • Engineering
  • Computer Science
  • Geology

Background:

  • Wireless sensor networks (WSNs) face localization challenges in complex underground coal mines due to signal fluctuations and node mobility.
  • Existing localization algorithms struggle with accuracy in dynamic and confined underground environments.

Purpose of the Study:

  • To develop a robust and accurate localization algorithm for WSNs in underground coal mine tunnels.
  • To address the limitations of current methods in handling signal variability and node movement.

Main Methods:

  • Proposed an iterative weighted centroid localization algorithm utilizing Received Signal Strength Indicator (RSSI) clustering.
  • Optimized RSSI data with K-means clustering to dynamically determine path loss parameters.
  • Integrated an improved iterative weighted centroid algorithm for high-precision positioning.

Main Results:

  • The proposed algorithm demonstrated superior performance compared to existing high-performance localization algorithms.
  • Achieved improved localization robustness across various scenarios, including changes in node communication radius, beacon node ratio, and tunnel width.
  • Validated through experimental data in complex underground mine tunnel simulations.

Conclusions:

  • The developed algorithm offers enhanced localization accuracy and robustness for WSNs in challenging underground environments.
  • Provides a valuable theoretical reference for three-dimensional localization in confined, elongated spaces like mine tunnels.
  • Contributes to improved safety and operational efficiency in underground mining through precise positioning.