A multidisciplinary approach for deploying a wildfire UAV fleet for Detection and Communication

Abstract

Wildfire constitutes a global crisis, with both frequency and severity increasing over the past several decades. In the United States, wildfires have emerged as a significant concern in the western regions, especially in California, Colorado, Hawaii, and along the West Coast of North America. Wildfires in Canada have produced smoke that has affected air quality as distant as New York in the United States. Australian wildfires have had severe impacts, affecting billions of animals, including koalas, kangaroos, and wallabies, in recent years. Wildfires inflict severe local damage on land and communities and present global challenges to interconnected natural ecosystems. These effects spread to natural resources and wildlife worldwide. As these threats progressively increase, early detection and communication become key in minimizing the adverse impact on wildlife, humans, and the environment. Numerous strategies are being evaluated for detecting and communicating about wildfires, but one of the most effective emerging tools is turning out to be unmanned aerial vehicles (\gls{uav}s). Not all UAVs are suited for the purpose of wildfire detection and communication, as most UAVs are designed for universal activities like security, agriculture, infrastructure monitoring and communication networks. Traditional general-purpose UAVs are not able to detect wildfire early because their deployment strategies, wildfire susceptibility assessment strategies, and UAV aerodynamics are not optimized for that specific purpose. During the evaluation of UAVs for the purpose of wildfire detection and communication, surveillance capability is the most significant factor if the goal is to develop an effective and cost-efficient solution. To consider an entire fleet of UAVs for wildfire detection and communication, we can determine surveillance capability only by understanding the overall system in a holistic way. We accomplish this understanding by deploying a comprehensive systemic approach with model‐based systems thinking (\gls{mbst}) to address this real-world complex problem. We also use both systemic and numerical techniques to come up with novel systems methods of addressing the specific challenges of wildfire. The research results show that the most efficient possible detection of wildfires compared to any state-of-the-art available strategies occurs using UAVs designed specifically for wildfire detection, with integrated UAV flight paths and a comprehensive deployment method. Outcomes for this research study demonstrate that existing generic UAV design elements, such as flight controls, airfoil aerodynamics, sensor packages, and communication schemes, are not optimized for wildfire. The systemic methods documented in this dissertation to address the problems of detecting and detecting wildfires enabled by the optimal deployment strategies (\gls{ods}) and wildfire point-optimization strategies (\gls{wpo}). This mission-oriented fleet deployment is also coupled with the most effective airfoil design, specifically developed to detect wildfires.