Smoke from WUI fires contains toxic chemical substances from the burning of synthetic compounds, making these fires especially dangerous. By employing swarms of drones to measure a range of toxic gases and aerosols in WUI plumes, this project will provide more accurate, real-time data on air toxics from WUI fires to further understand their impact on human health.
In the long term, Kong plans to harness the potential of automated technology to take wildfire management from passive response to proactive prevention. Along with the hybrid aircraft to monitor hazardous sites, his team is creating an integrated system of ground sensors and UAVs to predict and detect wildfires before human intervention is necessary.
“It has to be satellites, watchtowers, UAVs, manned aircraft, ground sensors, all the mechanisms working together in order to have a system to predict and detect wildfires,” said Kong.
Co-investigators on the Seed Award included Anthony Wexler and Thomas Young at UC Davis and Deborah Bennett at UC Davis Health.