Using Wildfire Simulations as Predictors for Economical Risk Management

Team: Jeremiah Hamlin (ME), Mikio LaCapra (ME), Carlos Nunez (IEOR)

Advisor: Tarek I. Zohdi (ME)

Wildfires have become an annual destructive force with the 2018 California wildfires witnessing the tragic loss of life and $3.5 billion in damages, which unraveled communities and motivated new outlooks to safety and liability. Our solution harnesses the novel firefighting technique of real time low computation wildfire prediction simulations, through a particle based representation of ember lofting dynamics and thermodynamics over real terrains. Not only does this simulation predict fire trajectory patterns to prevent hazardous scenarios, it can be paired with historical data for economical risk management such as assisting insurance companies establish rates based on the burn risk of a property.

Real Time Simulations:

Simulations are a novel reactive and proactive fire fighting technique. We spoke with firefighters and studied examples of non computationally intensive models they could use.

Weather-based ML Model:

Complementing the simulation, weather data and machine learning models are used to predict wildfire probability across the stat.

Industry Analysis:

An industry analysis is conducted of current solutions in simulations, satellite imaging, and UAV mapping companies.

First Responders as Target Users

Firefighters organizational structure and access to data drives the local environment simulation needed.

Applicable Markets and Partners

Establishing partners in simulation and imaging combined with customers in insurance companies to develop a realistic outlook in the private sector.