## 2 Literature Review
### Discussion
#### 2.2.2 Unmanned Aerial Vehicles (UAV)  
UAVs commonly refer to vehicles or systems that are remotely operated and travel by flight. The data gathered by UAVs are often in real-time, accurate and provide unique vantage points that would otherwise be inaccessible, dangerous or time-consuming to obtain by emergency responders. This is attributed to the mobility of the UAVs, which allows rapid and continuous visual monitoring throughout the fire's progression and movement. While UAVs may define any unmanned aerial vehicle such as military drones, the majority of them that were first designed for wildfire fighting purposes were comparable to consumer or hobby drones, operating within 1000-4000 feet, as shown in Figure 4[53]. This range has increased to 30,000 ft as drone technology has commendably progressed in the past years[54]. The data collected commonly take the forms of GPS location, images, video feeds or readings from sensor nodes such as those described in the previous section[55]. These systems may be remotely controlled by humans or automated systems. Automated systems are easily adaptable by users with little to no experience compared to a system that requires human pilots. For example, Fotokite Sigma can follow a programmed flight path set through an application on a mobile device[56]. This is particularly useful for applications such as detecting wildfires, where the autonomy is a necessity to support persistent vigilance. A few years ago, autonomous UAV were limited to low-complexity surveillance tasks but have now been vastly improved by researchers. [PERSON] et al. discuss a system where fleets of different types of semi-autonomous drones are deployed in stages to search, confirm and observe fires[57]. Although each drone may not handle dynamic and complex tasks such as those with dedicated pilots, the autonomy allows for quick commanding and organization within a fleet regardless of its size. With general usages laid, a UAV system's main limitation is summarized by its relatively low-capacity power source. This is due to the structural constraints limiting usage of heavy energy-dense batteries. UAVs are usually outfitted with various cameras (videos, IR and imaging) but may contain many other features depending on the designer[55]. For example, some systems are capable of controlling a fleet of UAVs. Others may have additional devices onboard, such as a specialized fire sensor or a tank of water[58]. The IGNIS system by Drone Amplified is an example of an advanced drone that utilizes several of these features[59]. It combats wildfires by initializing backfires through chemical payloads, and can be actively controlled by both remote controller and/or by preset instructions sent by a mobile app. Several data processing algorithms have been proposed to process the video feed from the UAV and swiftly detect the presence of active wildfires, intens  
Figure 4: Possible roles of UAVs. (Images sourced from Creative Commons, following the guidelines on Attribution 3.0 Unported, CC By 3.0[26]. The only modifications to the images are cropping and resizing). of spread. [PERSON] et al., employed a Kalman filter-based approach that uses only the UAV position and temperature recorded at each sampling point to identify a wildfire and predict the fire-spread behavior [60]. The performance of this model with multiple vehicles was observed to be comparable to the results obtained with the FARSITE benchmarks, with less computational cost. [PERSON] et al., proposed a combined UAV-IoT system as a more cost-effective solution than satellite surveillance. In a fire event, the ground-based IoT devices in the vicinity of the wildfire generate alarms to the UAVs nearby, which then verify the fire probability to avoid misdetections [61]. The authors designed an algorithm to optimize the IoT density and number of UAVs to minimize the cost of resources while also maximizing the fire detection probability.