## 1 Introduction
### Motivation  
Due to various factors, SAR relies on human rescuers, which may not be sufficient in many circumstances. To begin with, the injured people are frequently not precisely found. The number of these people and their present medical condition and necessary medical gear for treatment are unknown to the rescue crew. Covering a large impact area, on the other hand, takes more time for human rescuers, especially in areas with bad weather and uneven ground situations. Poisonous gases, flames, radiation, high temperatures, biohazards, and other risks in the impacted region also pose a significant threat to rescuers. UAVs are distinguished from conventional vehicles by their cost-effectiveness, ease of use and maintenance, affordability, market availability, and ease and speed of entry to disaster areas [30] The operation of manned aerial vehicles demands highly skilled individuals, and their usage involves costly preventative and corrective maintenance to maintain the aerial vehicle and pilot's safety. Furthermore, take-off and landing locations, typically located far from the SAR region, are subject to rigorous limitations. As a result, the employment of ground vehicles in SAR missions has been advocated [31]. However, the size, weight, and cost of batteries used to power ground vehicles contribute to the overall cost. In addition, ground vehicles have limited mobility and have trouble overcoming obstacles and obstructions. As a result, ground robots are not guaranteed to go outside cities. They also necessitates strict real-time control by the operator, as a tiny delay in control command transmission causes the robot to wander, potentially causing damage to the robot or its surroundings. In addition, real-time video of the robot's surroundings should be sent to the human operator, and this is a bottleneck in bandwidth and transmission power. The employment of UAVs for medical missions has been proven to be effective. Many studies have introduced the use of UAVs to deliver medication to rural areas and transport medical products over long distances, such as blood derivatives and pharmaceuticals [30], microbiological specimens and biological samples [32], and defibrillators to out-of-hospital heart attack victims [33]. The employment of UAVs outfitted with electro-optical sensors and processing modules might assist in overcoming the present weaknesses of traditional man-dependent systems and those of UAVs and ground robots. Furthermore, UAVs can play a leading role in providing real-time, on-demand, and trustworthy information, which is crucial in rescue and search operations due to the speed of data collection and processing. Human detection using AI approaches, on the other hand, has been the subject of multiple studies. The Support Vector Machine classifier (SVM) was utilized to obtain the highest performance combining both feature descriptors. Reference [34] proposed using a Convolutional Neural Network (CNN)-based system to recognize and locate human positions inside surveillance camera material. In [35], the authors propose using a combination of the intensity histogram local binary pattern to distinguish between human and animal detection. The proposed approach in [35] uses a deep CNN to construct a quick deep learning classification system.