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Research on fire assessment during robot-assisted downhole rescue based on the fusion of human and artificial intelligence

Author

Listed:
  • Liu, Weiwei
  • He, Runfeng
  • Liu, Yuqi
  • Jiang, Song
  • Fang, Jiayi
  • Zhu, Xiaoyu
  • Wu, Liangliang
  • Lu, Fang

Abstract

Primary disasters in underground mining tunnel networks can cause structural damage and electrical failures, potentially leading to localized fires that could escalate into regional underground fires. To prevent severe secondary disasters, it is essential to assess the risk of secondary fires in post-disaster underground areas and determine appropriate rescue and mitigation strategies. This study proposes an underground secondary fire monitoring and evaluation method integrating artificial intelligence–human intelligence (AI–HI) fusion concepts. AI visual algorithms on mobile robot platform detect secondary fires post-disaster, transforming real-time fire conditions and location information into key fire-risk assessment parameters. The method also incorporates both long-term prior and short-term feedback from the disaster. By combining these factors with HI criteria, a fuzzy comprehensive evaluation model for underground fire risk is constructed. This model enables real-time sensing and assessment of secondary fire risks, providing location-based risk-level evaluations to support rescue decision-making. A case study of an underground mine in China demonstrates the method's application, showcasing its effectiveness in perceiving secondary fire risk distribution in modern underground mines with complex tunnel structures.

Suggested Citation

  • Liu, Weiwei & He, Runfeng & Liu, Yuqi & Jiang, Song & Fang, Jiayi & Zhu, Xiaoyu & Wu, Liangliang & Lu, Fang, 2026. "Research on fire assessment during robot-assisted downhole rescue based on the fusion of human and artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 223(C).
    • Handle: RePEc:eee:tefoso:v:223:y:2026:i:c:s0040162525004895
    DOI: 10.1016/j.techfore.2025.124458
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    References listed on IDEAS

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    1. Kai Wang & Shuguang Jiang & Xiaoping Ma & Zhengyan Wu & Hao Shao & Weiqing Zhang & Chuanbo Cui, 2016. "Numerical simulation and application study on a remote emergency rescue system during a belt fire in coal mines," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(2), pages 1463-1485, November.
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