Wildfires and power grids are deeply interconnected—fires damage electrical infrastructure, incurring high repair costs and economic losses, while power lines are a major ignition source. In Southern California, where dry conditions, strong winds, and dense vegetation heighten wildfire risks, understanding this relationship is essential.

Government agencies and electricity companies suffer significant financial losses from grid failures, legal liabilities, stock fluctuations, and fire victim compensation funds, yet mitigation efforts remain reactive rather than proactive. A quantified cost-risk assessment can incentivize governments and power companies to adopt a strategic, preventive approach to wildfire mitigation.

This project bridges that gap by leveraging machine learning to analyze wildfire-power grid interactions, predict financial losses, and offer actionable insights to optimize infrastructure and reduce economic damage.