Author(s): Evan Twarog, Stanford University (First Author, Presenting Author) Daniel Neamati, Stanford University Grace Gao, Stanford University
Prescribed fires help manage land, but their smoke can affect nearby communities—especially in hilly or coastal areas where wind and terrain make smoke movement hard to predict. This project, in collaboration with Stanford’s SMesh Project, explores how to place smoke sensors more effectively around burn sites by simulating smoke behavior under many possible wind conditions, accounting for forecast uncertainty. By testing our method at sites in Malibu, Shasta, and Henry Coe State Park, we found smarter ways to position sensors and reduce the chances of missing key smoke data. Our approach will be tested during real prescribed fires in Fall 2025 to help improve air quality monitoring.
