This Engineering Research Initiation (ERI) award supports research to develop an early wildfire detection system using autonomous unmanned aircraft systems (UASs) to provide a low-cost, flexible, and timely solution for identifying wildfires at their earliest stages. As wildfires become increasingly frequent and destructive across the United States, there is a critical need for detection methods that can identify fires before they grow out of control. Traditional approaches, such as satellite monitoring, manned aircraft surveys, and remote camera surveillance, often suffer from limited resolution, delayed response times, and high operational costs. This project introduces a dual-sensing strategy by equipping UASs with both visual and olfactory sensors. Similar to how humans can smell smoke before seeing flames, the proposed UAS would detect smoke particles and chemical signatures before visual evidence becomes apparent. The ability to trace smoke back to its source, even in low-visibility conditions such as heavy smoke or nighttime, would enable faster and more accurate fire identification. The successful outcome of this research will impact broader applications beyond wildfire detection, such as chemical leak detection and other environmental monitoring tasks. Additionally, the project will foster interdisciplinary collaboration between engineering, environmental science, and forestry, while also providing educational opportunities for students through hands-on research and