Published Paper Details:

The intersection of satellite imagery analysis and transmission line monitoring offers a transformative approach to vegetation management in power infrastructure. This study employs the YOLOv8 algorithm to detect and analyze trees encroaching upon transmission lines, leveraging the high-resolution capabilities of satellite imagery. By automating the identification process, this methodology enhances the efficiency and accuracy of vegetation monitoring, enabling proactive maintenance to mitigate potential risks to the transmission network. Through the integration of advanced technologies, such as machine learning and remote sensing, this research aims to optimize infrastructure resilience while ensuring uninterrupted power transmission. Furthermore, this abstracted approach not only streamlines vegetation management processes but also contributes to the overall reliability and safety of transmission infrastructure. By harnessing the power of satellite imagery and machine learning algorithms, utility companies can effectively identify and address vegetation encroachments in a timely manner, minimizing the risk of outages and enhancing system resilience. The proactive nature of this methodology enables utilities to prioritize maintenance efforts, allocate resources efficiently and ultimately improve the reliability of power transmission networks in the face of dynamic environmental challenges.