### Related Work  
New technologies in the field of UAV swarms have recently been the focus of many scientists and large corporations. Surveys of published papers have also been conducted to provide comprehensive information on UAV swarms. In this section, we discuss some of  
Figure 1: Some typical applications of UAV swarms. the latest relevant surveys conducted in this field. They focus heavily on communication technology and the application of AI to effectively control UAV swarms. Increasing the coverage area using UAVs is one of the important research areas. Many technologies have been developed to provide better coverage areas using UAV networks. A detailed survey in [18] highlights various issues from the coverage perspective of UAV networks. The authors classified the issues into groups and mentioned various limitations. The findings of the survey highlight the need for further in-depth studies to explore the coverage area of UAV networks. Another survey conducted in 2023 addressed the limitations of ground infrastructure as the number of devices increases [16]. Utilizing the flexibility of UAVs, the authors evaluated the use of UAVs to improve IoT network performance. UAVs provide wireless access to devices when the ground network is overloaded or disconnected. AI-based methods for optimizing, scheduling, and orchestrating UAV-supported IoT networks were investigated. A comprehensive analysis was conducted on the influence of implementing advanced AI architectures, models, and methods on various features of IoT networks. Due to the stringent and complex requirements of UAVs, cloud-based AI models are increasingly difficult to meet. Therefore, the authors of the study [19] focused on edge AI models, which are AI models running on devices or servers close to users. This model fully exploits the strengths of UAVs in improving IoT services. Complete analyses were conducted on the influence of edge AI on UAV characteristics such as autonomous navigation, security and privacy, computer vision, and communication. The authors also focused on current prominent applications of swarm UAVs, such as distribution systems, civil infrastructure inspection, smart agriculture, search and rescue (SAR) operations, and wireless communication base stations (BS). Generative artificial intelligence (GAI) has been proposed and investigated in [20]. In their work, the authors reviewed the key technologies of GAI and its important role in UAV networks. The method applies GAI to improve communication and networking efficiency and security of UAV systems. This study also proposed a new framework of GAI for advanced UAV networks by estimating the spectrum map supporting UAVs and optimizing the transmission rate based on the proposed framework. For example, based on the data collected from a part of the target area, GAI takes into account the limited resources of the UAV to accurately infer the status of the entire area. This allows for reasonable resource allocation and trajectory planning. Awareness of environmental changes and the ability to adapt to mission requirements quickly are key to successful UAV deployment [21]. Therefore, in [22], a new study in 2024 focused on UAV-centric ML solutions. This study examined how well they meet the network requirements, considering the changing roles, collaboration, cooperation, and context of UAV networks. Solutions were proposed for air-to-air, air-to-ground, and ground-to-air communications, as well as mobile edge computing. The survey highlighted the urgent need for UAVs in emerging 5G/6G networks. A recent study [23] provides an in-depth survey of UAV-enabled integrated sensing and communications (ISAC). In the context of 6 th-generation (6G) wireless networks, UAVs are deployed as airborne wireless platforms to provide better coverage. At the same time, they meet the advanced sensing and communications (S&C) services. However, due to the size, weight, and power (SWAP) constraints of UAVs, the application of UAV-enabled ISAC opens new opportunities and challenges.