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

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.

Authors

Publication Details

Journal
International Journal of Low-Carbon Technologies
Published
2025-01-01
DOI
https://doi.org/10.1093/ijlct/ctaf036
Primary Topic
Power Line Inspection Robots
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Zhaoyu Tao, Yang Wang, Jin Pan, Weiguo Li et al.
International Journal of Low-Carbon Technologies
Power Line Inspection Robots
article

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

Zhaoyu Tao, Yang Wang, Jin Pan, Weiguo Li, S.K. Wang, Chong Ling Duan
article en

Abstract

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.

International Journal of Low-Carbon TechnologiesVol. 20
Openalex Percentile: Top 95%
Power Line Inspection Robots
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Research on a low-carbon aerial ropeway construction safety monitoring system for transmission line engineering freight based on deep learning — Zhaoyu Tao, Yang Wang, et al. · International Journal of Low-Carbon Technologies (2025) | TGRS Research Map | TGRS