## 1 Introduction  
Over the last few decades, many countries have suffered considerable casualties and economic losses because of the high frequency of miscellaneous natural disasters. Natural disasters have recently caused enormous damage, resulting in crisis circumstances that have jeopardized people's lives. One of the fundamental reasons for such huge losses is the lack of an efficient disaster relief network management system to support rapid emergency information diffusion. Disaster management, Search and Rescue (SAR) missions, and health monitoring are critical applications that require the localization of objects with high precision, sometimes promptly. During and after disasters, central management systems and infrastructure, including communication Base Stations (BSs), can be destroyed, causing insufficient availability of essential resources and the delinquency of communication links. It may take a few days to many weeks to re-establish a functioning communication backbone for telecommunications and internet services to restart. Therefore, it is essential to engage emerging and upcoming technologies to restore emergency communication networks. Furthermore, during natural disasters, SAR must maintain contact with each other, the control center, and the victims; victims must broadcast their whereabouts and receive rescue information in a closed-loop system. With controllable mobility, low cost, and strong Line-of-Sight (LoS) links, Unmanned Aerial Vehicles (UAVs) are envisioned as essential to emergency information diffusion by acting as flying BSs to serve terrestrial users losing connection to ground BSs. The employment of UAVs in SAR missions significantly reduces effort, financial costs, and time spent, while possibly saving human lives. UAVs can operate as flying BSs to offer emergency wireless services in disaster-affected areas to tackle this challenge [1]. A collection of UAVs can be employed to identify events on city highways for emergency vehicle assistance, as depicted in [2]. UAVs provide valuable information to the rescue troops, speeding up the rescue operation. A robust routing mechanism ensures communication stability while sending the distress information. In [3], the authors introduced a revolutionary UAV route planning framework for emergency message delivery and gathering. While visiting access sites to send and collect emergency alerts, mobility and transmission power are maximized. Moreover, [4] proposed a UAV-assisted Wi-Fi network to aid- people working at relief centers in gathering surveillance data. The planned network intends to speed up rescue efforts and give up-to-date disaster information. The capacity of UAVs to carry a variety of equipment and traverse lengthy periods speaks of their fast expansion into civilian sectors other than surveillance and aerial photography. UAVs equipped with electro-optical sensors, real-time processing modules, and advanced communication systems demonstrate a novel low-cost solution for enhancing government authorities' and rescue agencies' current capabilities in detecting and locating wounded and missing people during and after disasters. The authors of [5] presented a way of obtaining information about a devastated region following a natural disaster. The process entails taking photos in real-time, marking their position and altitude, and transferring the image with flight characteristics to a ground control station to create a three-dimensional danger map. In disaster relief networks, only local information can be utilized in autonomous decision-making, which may degrade the performance attained by game-theoretic methods. Some existing works have resorted to graph theory to solve the dynamic resource allocation problem with tractable complexity. The authors showed how UAVs equipped with vision cameras might help with avalanche SAR operations [6]. The process took advantage of Machine Learning (ML) techniques.