Factor This From reactive to predictive: Reimagining wildfire mitigation efforts for utilities
Mar 9, 2026
Don McPhail, VP of Market Development at eSmart Systems with ~20 years in energy, spotlights AI-driven imagery and digital twins for grid resilience. He discusses shifting from asset-focused fixes to community-first planning. Conversation covers how high-res imagery reveals tiny defects, why AI finds more issues, and how digitization creates audit trails and measurable value.
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AI Turns Imagery Into Component Level Risk
- AI-powered computer vision turns drone, helicopter, and crew imagery into component-level asset health insights.
- eSmart Systems' GridVision identifies defects and combines with fire/wind models to prioritize preventative mitigation ahead of wildfire or storm season.
AI Helps Avoid Overbuilding Transmission
- Transmission planning must balance new generation, distributed energy, and rising demand using AI-driven forecasting and grid-enhancing technologies.
- AI and big data help avoid over-specifying the grid while optimizing lead-time-heavy interconnection planning.
Use Affordable Sensors Paired With Scalable AI
- Adopt cheaper sensors, drones, and satellite imagery now because costs and compute capacity have dropped significantly.
- Pair those data sources with scalable AI pipelines so utilities can act on patterns rather than just collect raw data.