<p>Integrating Unmanned Aerial Vehicle Remote Sensing With Internet of Things Frameworks: A Survey of Methods and Applications</p>

Remote sensing has gained significant attention in recent years due to the increasing availability of cloud computing platforms for geographically dispersed sensor sites. Within the Internet of Things (IoT) paradigm, data generated by sparsely deployed sensor networks in remote locations is transmitted through various telemetric communication channels. One of the most effective and widely adopted approaches for data collection and transmission from IoT-based sensor environments is the use of Unmanned Aerial Vehicles (UAVs), which provide high mobility, cost-effective surveillance, low deployment cost, and time efficiency. In addition to conventional cloud support, the recent convergence of Edge Computing and Artificial Intelligence has further enhanced UAV-enabled remote sensing by enabling real-time data processing, intelligent analytics, and reduced latency in distributed environments. This review article examines the advancements, challenges, and emerging opportunities associated with integrating UAVs into IoT-driven remote sensing systems. It explores the diverse range of sensing technologies and their applications across domains such as agriculture, smart cities, natural disaster monitoring, infrastructure management, and search-and-rescue operations. Furthermore, critical challenges, including regulatory constraints, data privacy concerns, scalability requirements, and interoperability issues, are discussed in the context of evolving intelligent and edge-enabled architectures. The objective of this survey is to provide practitioners and researchers with a comprehensive understanding of UAV-assisted remote sensing within IoT ecosystems while highlighting open research issues, technological trends, and future directions.