Utility Pole Fire Risk Inspection from 2D Street-Side Images
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 9 references that are in the map. First posted on arXiv 19 Jun 2024.
Builds on
2 of 9 references.
References · 2
- 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,852
- 2024Depth Anything: Unleashing the Power of Large-Scale Unlabeled Datacited by 1,360
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