AI-powered aerial robots capture wildfire smoke data with precision

Researchers at the University of Minnesota Twin Cities have developed AI-powered aerial robots—coordinated drone swarms equipped with sensors—that can fly directly into wildfire smoke plumes to collect high-resolution, real-time data. Unlike traditional drones, these robots use artificial intelligence to detect and track smoke, enabling them to gather multi-angle data and create 3D reconstructions of smoke dispersion. This detailed information helps scientists better understand smoke particle composition and movement, which is crucial since smaller particles can travel long distances and impact air quality far from the fire source. The system offers a cost-effective alternative to satellite monitoring and aims to improve predictive models for wildfire smoke behavior and hazard response. The technology addresses limitations in previous smoke modeling and field data collection by providing real-time flow pattern analyses and particle characterization through Digital Inline Holography. Beyond wildfires, the researchers envision applications for monitoring other airborne hazards like sandstorms and volcanic eruptions. Future goals include developing the system into a practical early fire detection tool to enable faster response