Object Detection using Unmanned Aerial Vehicles: Challenges and Opportunities

Unmanned Aerial Vehicles (UAVs), more often known as drones, have lately gained significant attention in the aviation sector because of the vast variety of potential applications they might have in areas such as surveillance, environmental monitoring, agricultural, and disaster management. The evolution of UAV-based object identification systems is the subject of this article. A better and faster way to recognize and categorize items from aerial photography is to combine UAV technology with advanced Computer Vision (CV) algorithms. The research explores several strategies, focusing on Deep Learning (DL) frameworks like Convolution Neural Networks (CNNs) and region-based approaches. It emphasizes how well these frameworks perform and adapt in complex and dynamic contexts. Issues with data transmission, real-time processing, and the impact of UAV flying characteristics on detection performance are also included in the study. The results indicated that object detection systems using UAVs have great potential to enhance situational awareness and decision-making in many different domains, which might lead to new developments and uses in the future.