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Goal: Researchers studying artificial intelligence have focused a lot of emphasis on computer vision in drones. Drones with intelligence can tackle a lot of issues in real time. For the purpose of monitoring particular surroundings, computer vision tasks like object identification, object tracking, and object counting are important. It becomes increasingly difficult to do, though, due to elements like motion blur, occlusion, camera angle, and altitude. Methodology: A thorough assessment of the literature on object identification and tracking with unmanned aerial vehicles (UAVs) in relation to various applications has been done for this research. This study highlights the research gaps and provides a summary of the results of previous studies. Contribution: Detailed and categorized object identification techniques are used in UAV photos. A selection of UAV datasets tailored to object identification tasks is provided. Summaries of current research projects in various applications are provided. In order to alleviate highlighted research limitations, a secure onboard processing system on a strong object detection framework in precision agriculture is finally presented.