A Review of UAV Applications in Electrical Transmission Line Inspection: Methods, Technologies, and Challenges
Abstract
This paper presents a comprehensive review of unmanned aerial vehicle applications in electrical transmission line inspection, focusing on methods, enabling technologies, and operational challenges. Traditional inspection techniques, including ground-based surveys and manned helicopter patrols, are often costly, time-consuming, and hazardous, thereby necessitating more efficient alternatives. UAV-based inspection systems have emerged as transformative solutions, offering enhanced accessibility, real-time data acquisition, and improved safety performance. The study examines key inspection methods, including visual imaging, infrared thermography, LiDAR-based scanning, and multispectral sensing, which enable fault detection, vegetation monitoring, and structural assessment. It further explores technological advancements in UAV platforms, such as autonomous navigation, artificial intelligence-driven image processing, and integration with geographic information systems for predictive maintenance. Despite these advancements, several challenges persist, including limited flight endurance, regulatory constraints, data processing complexity, cybersecurity risks, and environmental factors affecting flight stability. The review highlights the need for robust communication systems, advanced battery technologies, and standardized regulatory frameworks to support large-scale deployment. Additionally, the paper identifies emerging research directions, including swarm UAV coordination, edge computing, and digital twin integration for smart grid applications. By synthesizing current knowledge and technological trends, this review provides valuable insights for researchers, industry practitioners, and policymakers seeking to optimize transmission line inspection processes and enhance power system reliability. The findings underscore the critical role of UAVs in modernizing infrastructure monitoring while emphasizing the importance of addressing technical and regulatory limitations to achieve sustainable and scalable implementation across diverse energy environments. Furthermore the integration of machine learning models enhances defect classification accuracy and reduces manual interpretation efforts in large-scale inspection datasets. Economic considerations, including cost-benefit analysis and lifecycle optimization, demonstrate the potential of UAV systems to significantly lower operational expenditures compared to conventional inspection approaches. However, issues related to data standardization, interoperability, and workforce skill gaps remain critical barriers to widespread adoption. Addressing these limitations requires multidisciplinary collaboration among engineers, regulators, and energy stakeholders to develop resilient and adaptive inspection frameworks. Ultimately, this review establishes a foundation for future innovations aimed at achieving intelligent, autonomous, and data-driven inspection ecosystems within modern power transmission networks, ensuring improved efficiency, safety, and operational resilience globally.
Keywords
UAV, Transmission Line Inspection, LiDAR, Thermography, Artificial Intelligence, Smart Grid, Predictive Maintenance, Drone Technology
Citations
IRE Journals:
Delali Dagodzo "A Review of UAV Applications in Electrical Transmission Line Inspection: Methods, Technologies, and Challenges" Iconic Research And Engineering Journals Volume 2 Issue 6 2018 Page 234-254 https://doi.org/10.64388/IREV2I6-1716083
IEEE:
Delali Dagodzo
"A Review of UAV Applications in Electrical Transmission Line Inspection: Methods, Technologies, and Challenges" Iconic Research And Engineering Journals, 2(6) https://doi.org/10.64388/IREV2I6-1716083
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