## 2 UAV-Enabled Disaster Management Strategies  
UAVs can change the way disaster mitigation is planned and prepared for, and how disasters are responded to and rebuilt from. To successfully respond to disasters and design a practical disaster management and prediction technique, it is critical to understand the nature of disasters and suitable strategies, as shown in Figure 2. UAVs can be used for different purposes while planning disaster management strategies such as mitigation, preparation, response, and recovery. In recent decades, the idea of disaster strategies have been used to define, plan, and analyze disasters and their respective emergency operations [36]. Thus, the most typical scope of disaster management strategy is the ongoing process of catastrophe management known as the disaster management cycle [36]. During a natural disaster, response time to disaster hazards is critical in preserving human lives, particularly those who live or work in the impacted regions.  
UAVs can aid SAR in disasters by enhancing the procedure of data gathering from the disaster environment via integrated sensors connected to UAV computing. The disaster environment catches individuals alive in the catastrophe region, while the UAV computing helps gather mission critical data for more effective and well-timed SAR operations [37]. The data collected is processed and analyzed by the UAV computing itself using intelligent  
Figure 2: Disaster management strategies.  
techniques for onward transmission. The SAR can now be coordinated and guided efficiently and safely based on the data analysis. This project employed UAV computing to detect disasters and devise expedited recovery measures. Furthermore, the UAV computing process flow is designed to gather data and to simultaneously transmit the information.  
During disasters, UAV computing plays a critical role in capturing data in real-time and reaching disaster areas, reducing economic losses and losses of life, both humans and animal, by providing onboard processing, storage, and network connectivity for disaster mitigation, with minimum UAV energy consumption [38]. In addition, UAVs' ability to fly closer to the disaster locations and surroundings with IoT devices and SAR makes them a critical disaster management choice. [PERSON] et al. [29] introduced UAVs to enable mobile computing with intelligence in several applications.  
During a disaster, collaborative UAV computing can be used to fly closer to SAR teams to provide efficient connectivity, detect things in the disaster zone, gather accurate data from the disaster locations, compute over short distances, save energy, and send data to SAR and the cloud. On the other hand, UAV computing partnerships are built on service delivery for delivering SAR to catastrophe zones, and to locate jobs in the surroundings. Understanding of tasks and contexts is dependent on UAV computing and collaborative processing. On the other hand, actual performance depends on the efficiency of the processing tools available in the UAV for real-time computing and processing.  
Artificial intelligence plays a vital role in improving computing in UAVs [39]. The UAV computing network collaborates to guide SAR and disaster centers using the collaboration concept for networked UAV computing intelligence collaboration, SAR, and disaster centers (nodes). The collaboration mode described involves UAV computing intelligence (e.g., UAV computing to UAV computing) or SAR to SAR, and vertical networking between UAV computing intelligence to SAR or to the disaster center. As a result, multi-UAV computing intelligence is networked and collaborated to allow the SAR team to reach disaster areas through a routine safety protocol [40]. For instance, UAV computing intelligence monitors SAR and communicates to detect disasters and identify the victims, alerting SAR using vertical networking between UAV computing intelligence and SAR.