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Enhanced sparrow search algorithm with DV-Hop for high-precision fire sensor localization in underground spaces

Author

Listed:
  • Jiang Li
  • Liliang Dong
  • Le Xu
  • Fangqiong Luo
  • Zhenkun Lu
  • Yajian Huang
  • Shenghan Wei

Abstract

Fire monitoring in underground spaces is critical for emergency response, yet traditional localization methods like DV-Hop suffer from significant localization errors due to hop count ambiguity and premature convergence in optimization. To address these issues, we propose an Enhanced Sparrow Search Algorithm with Improved DV-Hop (ESSADV-Hop) method. The method incorporates a golden ratio-based communication radius division strategy to refine hop count granularity and an enhanced sparrow search algorithm with Gaussian perturbations to escape local optima. Experimental results show that ESSADV-Hop reduces the average localization error by 55.7% compared to DV-Hop (from 0.2910 to 0.1288) and outperforms other variants by 11.74%∼23.05% in accuracy, demonstrating its effectiveness for fire sensor localization in complex underground environments.

Suggested Citation

  • Jiang Li & Liliang Dong & Le Xu & Fangqiong Luo & Zhenkun Lu & Yajian Huang & Shenghan Wei, 2025. "Enhanced sparrow search algorithm with DV-Hop for high-precision fire sensor localization in underground spaces," PLOS ONE, Public Library of Science, vol. 20(12), pages 1-18, December.
    • Handle: RePEc:plo:pone00:0338706
    DOI: 10.1371/journal.pone.0338706
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