Monitoring Canada's enormous boreal forest for signs of fires is a daunting task. In the coming years it will likely be even more challenging as climate change leads to hotter, drier and longer fire seasons.
Youmin Zhang is a professor at the Gina Cody School of Engineering and Computer Science in the Department of Mechanical, Industrial and Aerospace Engineering and the Concordia Institute of Aerospace Design & Innovation. He believes there is a way to make the job easier and much cheaper.
In a paper he delivered at the 3rd International Symposium on Autonomous Systems, Zhang outlines the ways unmanned aerial vehicles (UAVs) popularly known as drones have been used to detect and monitor forest fires. He suggests how they can be used going forward to improve on more traditional methods such as watchtowers, satellite imagery, human-piloted flight patrols and human-walking patrols.
Zhang and his co-authors, Anim Hossain and Chi Yuan, both his students, point out that UAVs are not susceptible to the shortcomings found in other methods. Temperature and smoke sensors need to be relatively close to a fire to detect it; watchtowers have limited visibility and have a high false alarm rate; satellites cannot continuously monitor one location; and human pilots can, after hours in the air looking at forest canopy, simply get bored. None of these methods can provide constant, real-time monitoring efforts that can help firefighters.
The authors identify three key tasks an effective UAV-based system must include to be considered useful. First, it should be able to detect forest fires. Second, it must be able to diagnose identified fires. And third, it must be able to predict fire behaviour.
