In recent years, California's electrical grid has confronted mounting
challenges stemming from aging infrastructure and a landscape increasingly
susceptible to wildfires. This paper presents a comprehensive framework
utilizing computer vision techniques to address wildfire risk within the
state's electrical grid, with a particular focus on vulnerable utility poles.
These poles are susceptible to fire outbreaks or structural failure during
extreme weather events. The proposed pipeline harnesses readily available
Google Street View imagery to identify utility poles and assess their proximity
to surrounding vegetation, as well as to determine any inclination angles. The
early detection of potential risks associated with utility poles is pivotal for
forestalling wildfire ignitions and informing strategic investments, such as
undergrounding vulnerable poles and powerlines. Moreover, this study
underscores the significance of data-driven decision-making in bolstering grid
resilience, particularly concerning Public Safety Power Shutoffs. By fostering
collaboration among utilities, policymakers, and researchers, this pipeline
aims to solidify the electric grid's resilience and safeguard communities
against the escalating threat of wildfires.

通过利用计算机视觉技术，在加州电力网络中借助谷歌街景图像识别电线杆和评估与周围植被的距离以及倾斜角度，这项研究提供了一个全面的框架，重点关注易燃的电线杆，以防止野火起火并做出战略投资决策来加强电力网络的韧性。