AI-Guided Drones Track Wildfire Smoke to Improve Air Quality Predictions

The research was recently published in Science of the Total Environment, a peer-reviewed scientific journal.

Why Better Smoke Management Is Needed

According to a 2024 Associated Press report, 43 wildfires resulted from 50,000 prescribed burns conducted between 2012 and 2021, highlighting the need for improved smoke management tools.

Previous simulation tools have worked to model the behavior of fire and smoke particles, but there were still limitations in accurately collecting data, modeling, and the current field tools used to observe these smoke plumes. In this paper, the researchers addressed the challenges in accurately modeling how smoke particles behave and spread during wildfires and prescribed burns.

Understanding Smoke Composition and Behavior

"A key step is understanding the composition of smoke particles and how they disperse," said Jiarong Hong, a professor in the University of Minnesota's Department of Mechanical Engineering and senior author on the paper. "Smaller particles can travel farther and stay suspended longer, impacting regions far from the original fire."

How the Aerial Robots Work

Using a swarm of AI-guided aerial robots, they captured multiple angles of the smoke plumes to create 3D reconstructions and analyze flow patterns. Unlike traditional drones, these aerial robots can identify smoke and navigate into it to collect data.

"This approach allows for high-resolution data collection across large areas, at a lower cost than satellite-based tools," said Nikil Nrishnakumar, a graduate research assistant with the Minnesota Robotics Institute at the University of Minnesota and first author of the paper. "It provides critical data for improving simulations and informing hazard response."

Applications Beyond Wildfires

The cost-effective technology has potential applications beyond wildfires and could be adapted for use in sandstorms, volcanic eruptions, and other airborne hazards. The team's next goal is to translate the research into practical tools for early fire detection and mitigation.

"Early identification is key," Hong said. "The sooner you can see the fire, the faster you can respond."

Next Steps and Technological Advancements

Previously, the team developed an autonomous drone system equipped with onboard computer vision and sensors to detect and track wildfire smoke plumes in real-time. Building on this, they will now be focusing on efficient plume tracking and particle characterization using Digital Inline Holography with coordinated multi-drone systems. They are also working on integrating a type of drone, called a fixed-wing VTOL (Vertical Takeoff and Landing), that can take off without a runway and can fly for more than an hour for extended-range surveillance missions.

Team and Funding

In addition to Hong and Nrishnakumar, the team included Shashank Sharma and Srijan Kumar Pal from the Minnesota Robotics Institute. The paper was supported by the National Science Foundation Major Research Instrumentation program. This work was done with the help of the St. Anthony Falls Laboratory.