# Computer Vision for Fire Detection on UAVs--From Software to Hardware
## 1 Introduction
Due to the fact of their movement in the air above obstacles, they have a larger optical range that covers a large area. However, as the height increases, the resolution of the sensors decreases. UAVs flying at low heights are able to detect easier fires over areas such as forests or residential areas. Based on the above and a proposed communication system or network, it is possible to detect a fire early by UAVs before it becomes hazardous to the environment. UAVs are very effective because they are suitable for supervision and monitoring applications and due to their flexibility and free movement in the aerial environment. In addition, in many cases, Synthetic Vision Systems (SVSs) are used. SVSs provide a computer-generated visualization of the environment, through the sensors, according to the path that the UAV follows or its position. These types of systems are very useful in cases where the operation of vehicles is done remotely through an operator. However, the use of these systems in autonomous navigation missions is also important and feasible. SVS systems provide an augmented visualization of non-physical constraints and exo/ego centered views [7; 8]. The camera with which the UAV will be equipped plays a very important role in the successful achievement of early fire detection. Without the necessary sensor equipment, such an application becomes impossible. Of course, it is not only the sensor that is very important but also the way in which the risk will be identified, the type of classification and all those procedures related to the data transfer to a server. The goal of this research was to examine the use of UAVs and the state-of-the-art Computer Vision techniques to improve efforts to detect and prevent fires. Fire is a very dangerous situation for humans and animals as well as for the environment itself. Therefore,the research in this field has to keep evolving in order to prevent any kind of unplanned or uncontrolled fires. The study presents the Computer Vision models, the corresponding UAVs and the mission processes and materials for detecting fires. This literature review presents the stages and equipment that can be included in a fire detection and classification plan. The main contribution of the review is the screening of the most-used types of UAVs, cameras, Computer Vision models and AI algorithms. Furthermore, the key components and techniques which improve the quality of the mission are presented. In addition, frameworks, software and the main datasets are also presented. It is noted here that the above emerged after a study of published scientific works of the last decade. The present work is organized as follows: Section 1 consists of the introduction which presents core meanings of UAVs. Section 2 describes fire detection using Computer Vision on UAVs and, more specifically, the related work and the fire detection framework. Section 3 describes the research methods used to construct this review, the way the research was executed, and the early statistics of the research. Section 4 presents the taxonomy of the hardware and software/methods of the research and the dataset subsection includes the literature used datasets. Section 5 contains the discussion on the results of the literature review. Finally, Section 6 summarizes the final conclusion of the literature review.