# A Novel Drone Design Based on a Reconfigurable Unmanned Aerial Vehicle for Wildfire Management
## 1 Introduction  
Wild land fires pose significant challenges to both ecosystems and human safety, necessitating innovative approaches for effective management and mitigation. Unmanned aerial vehicles (UAVs), commonly known as drones, have emerged as invaluable tools in addressing various aspects of wildfire and prescribed fire science. As highlighted in the results published in the paper by [PERSON] et al. [1], a range of payloads attached to UAVs can be effectively utilized in forest fire and post-fire monitoring scenarios. The use of UAVs in various contexts offers substantial benefits, including cost reduction, temporal and spatial flexibility, high-precision data acquisition for tasks such as data collection and mapping, rapid damage assessment, and the inherent advantage of avoiding human risk [2]. For instance, LiDAR sensors can be utilized to map areas with higher biomass fuel concentration and to capture small changes in micro topography [3], as well as for characterizing and modelling power lines and for monitoring surrounding vegetation. As reported by [PERSON] et al. in their study [4], high-voltage power lines canrepresent a hazard, causing or increasing the intensity of forest fires. The most recent studies have tended to use LiDAR devices onboard, as they provide a higher density of points and particularly good performance for digitizing power lines and calculating vegetation heights and volumes to estimate fuel models. Additionally, RGB and thermal infrared (TIR) cameras can assist in the monitoring of hotspots [5; 6; 7], the recognition of persons and animals [8], or even enhancing the management of field teams [9]. Forest restoration and recovery in post-fire scenarios is crucial for improving/studying recovery and measuring fire severity, allowing quicker intervention [10; 11]. In this context, TIR sensors as sensing payloads have proven useful for real-time fire monitoring, while multispectral sensors have demonstrated potential in post-fire forest rehabilitation [12]. In wildfire management, UAV architecture is tailored for rapid deployment, versatility, and robust data acquisition. Fixed-wing UAVs excel in long endurance and broad coverage, making them ideal for initial wildfire detection and continuous monitoring [13]. Multirotor UAVs offer maneuverability and precision, essential for navigating complex terrains and assessing fire-affected areas in detail [14]. Integrating multi-UAV systems enables cooperative surveillance, ensuring quality of service and efficient resource allocation [14]. These UAVs are typically part of a larger network including ground stations that manage communications, control, and critical data processing for timely and effective wildfire response. Recognizing the diverse applications of UAVs, there arises a need for a multipurpose drone. Such a drone should be capable of hosting all these diverse payloads, regardless of weight, and possess the adaptability to change its configuration and payload swiftly. The ability to make rapid adjustments is crucial in circumstances where time is of the essence, optimizing the drone's efficiency and effectiveness in addressing the complex challenges posed by wildfires and their aftermath. To meet these multifaceted demands, the field of UAV development is rapidly advancing in its design approaches, with application of computer-aided techniques (CAx) leading the innovation charge. The integration of CAx techniques and innovative design approaches plays a pivotal role. [PERSON], [PERSON] et al. [15] demonstrated this through their conceptualization of a multi-rotor UAV with variable paddle pitch, leveraging CAx tools for optimization prior to prototyping. [PERSON], [PERSON] et al. [16] furthered this notion by employing generative modelling to automate design variations, enhancing efficiency and adaptability in the design process.