Integration of IoT-enabled UAVs in Smart Agriculture: Types, Applications, Trends, challenges

Unmanned aerial vehicles (UAVs) have garnered increasing attention in recent years due to their utilization of artificial intelligence (AI) technologies and automation processes. These vehicles are being developed for various applications, including the military, smart agriculture, rescue operations, entertainment, monitoring, and medicine delivery. In the current era, UAVs extensively employ a wide range of technologies to transmit data to base stations. The collected data undergoes processing, producing remarkable outcomes through the integration of machine learning and deep learning technologies. This paper reviews disease identification and object detection techniques and their associated applications & challenges. Additionally, the research explores recent trends and technologies in the field of smart agriculture. This research emphasizes the use of sensors in unmanned aerial vehicles (UAVs) by analyzing the methods utilized for recognizing diseased areas and things while identifying insects and sick crops. This paper also addresses the challenges encountered by existing methodologies and proposes directions for future research and development. Furthermore, this review delves into suitable techniques for heterogeneous UAVs and examines IoT-related strategies.