## 2 Related Work  
UAVs, including drones, are increasingly seen as innovative solutions for rapid search-and-rescue operations. They could provide many satellite advantages, but without the distance penalty. Receivers may experience a better signal quality as the system offers line-of-sight (LoS) communications and, hence, less propagation delay in relation to satellite systems [10; 11]. Our review of relevant literature reveals that there has been some consideration of the capabilities of drones for emergencies, including different cameras, propagation models, altitudes, and search patterns. This section then concludes with a review of related research, and highlights this paper's motivation. The most critical requirement for search-and-rescue teams to be able to save people's lives is having high-performance communication links. The authors of [11; 12; 13; 14; 15] focused on proposing different propagation models that could provide robust wireless communication between aerial stations and interdepartmental headquarters, including rescue teams. Hata and Okumura are typical empirical models, while air-to-ground and free-space are typical deterministic propagation models. These propagation models can measure path loss (PL) and coverage, which in turn are important parameters for monitoring wireless system performance and network planning. The results of using these propagation models in various emergency scenarios show that they exhibit advantages in relation to high altitude, wide coverage range, and adaption across different terrains. However, there are some shortcomings of existing models that should be addressed to enhance resilience and offer better quality of service (QoS) in harsh environmental conditions. Utilizing a drone to detect humans and their location in real-time disastrous situations is simulated and experimented in [16]. The proposal aims to identify the location of survivors buried under wreckage using a camera module, a microcontroller, and a sensor. The results show that the drone with its payload can be a vital and cost-effective tool for detecting victims who are still alive in harsh environmental conditions. In [17], re-searchers introduced a drone prototype for intelligent search, rescue, and disaster recovery missions. A colored camera, a GPS sensor, machine learning, and image processing were the tools used to carry out the missions. The results show that the proposed prototype can operate autonomously and quickly for search operations. A lifeguard drone flying at a 100 m altitude was designed to alert divers at beach locations and deliver an automatic inflating vest to drowning victims [18]. The initial call is started by a swimmer, who wears wristband, so they can press a button on the device; the drone can then the location using a GPS and ZigBee transmitter. The experimental results show a reasonable response from the drone. However, the use of a HD camera along with artificial intelligence are recommended to enhance the work. The authors of [19] proposed an automated human detection system mounted on a drone, with components including RGB camera and GPS sensor, for search-and-rescue missions. The system aims to offer rapid localization and allocate a score of confidence for each detection. At a 15 m altitude, the results show moderate accuracy in detecting persons with a higher level of confidence. A fully autonomous drone equipped with human detection sensors, communication modules (e.g., GSM/GPRS module, GPS), and an object collision detection sensor for search-and-rescue operations is discussed in [20]. At a 7 m altitude, both simulation and trials have shown that using inexpensive and reliable sensors such as passive infrared (RIP) sensors, ultrasonic sensors, and Arduino microcontrollers offered the ability to detect humans trapped under ruins. However, the paper recommends thermal cameras and advanced sensors to enhance the accuracy and response times.