Utility Pole Fire Risk Inspection from 2D Street-Side Images

TL;DR

This paper introduces a computer vision-based framework using Google Street View images to identify and assess utility poles' wildfire risk factors, aiding in proactive infrastructure management and wildfire prevention.

Contribution

The study develops a novel pipeline leveraging publicly available imagery to evaluate utility pole conditions and surrounding vegetation, enhancing wildfire risk assessment capabilities.

Findings

Successfully identified utility poles and vegetation proximity from street images.

Enabled early detection of high-risk poles to prevent wildfire ignition.

Supported data-driven decision-making for infrastructure resilience.

Abstract

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.