Compact UAS Sensor for Distributed Mapping of Wildfire Plumes

Wildfire frequency and severity is increasing across the US. Simply throwing more resources at the problem while doing things the same way is not a cost-effective solution to the wildfire crisis. Uncrewed Air Systems (UAS) provide the opportunity to conduct operations at night and in degraded visual conditions when firefighting conditions are more favorable but crewed assets are grounded. However, there are many hazards associated with operating UAS around wildfires at night including dangerous wildfire plumes. This research focuses on tackling the problem of detecting, mapping, and avoiding the high energy wildfire plume. Plumes contain extreme temperatures, severe updrafts and windshear to include firenadoes and areas of zero visibility. We propose a novel UAS compatible sensor for real time distributed mapping of plumes using Long Wave Infrared (LWIR) sensing technology. A 3D plume model will be assembled from multiple viewpoints similar to a 3D Radon transform. Onboard “edge” processing will allow local sense and avoid capability to support UAS autonomy. The 3D plume data will support digital twin Common Operating Pictures that facilitate second shift operations from a common fire model. By shrinking the sensor to sUAS size and leveraging low-cost Commercial Off the Shelf (COTS) components, the payload will be able to be placed on every crewed and uncrewed asset participating in the firefight. The research also applies to other emergency airspace operations where use of UAS for response to chemical spills, tornadoes, radiological events and volcanic activity will benefit from the capability to sense and avoid plumes. The proposed research can directly support the NASA FireSense and ACERO wildfire projects. In addition, commercial UAS operators are rapidly expanding wildfire services. The proposed plume mapping sensor will enhance revenue streams for these commercial operators.