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Research on a low-carbon aerial ropeway construction safety monitoring system for transmission line engineering freight based on deep learning

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Listed:
  • Weiguo Li
  • Yang Wang
  • Chaohua Duan
  • Jin Pan
  • Shouchang Wang
  • Zhaoyu Tao

Abstract

With the expansion of freight aerial cableways in mountainous regions, safety monitoring becomes crucial. Traditional methods are inefficient and lack intelligent warning systems. This paper proposes SafeRopeSystem, a deep learning-based safety monitoring system. It utilizes an edge-cloud architecture with SafeRopeNet, a lightweight target detection network enhanced by an Adaptive Feature Enhancement Module and a Weather-Robust Feature Pyramid Network for resilience in adverse weather. The system includes SafeHead for efficient detection and adaptive channel pruning for edge optimization. Cloud platforms provide data analysis and decision support, improving safety with reduced costs and high accuracy.

Suggested Citation

  • Weiguo Li & Yang Wang & Chaohua Duan & Jin Pan & Shouchang Wang & Zhaoyu Tao, 2025. "Research on a low-carbon aerial ropeway construction safety monitoring system for transmission line engineering freight based on deep learning," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 20, pages 771-780.
    • Handle: RePEc:oup:ijlctc:v:20:y:2025:i::p:771-780.
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    File URL: http://hdl.handle.net/10.1093/ijlct/ctaf036
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