<p>Precision drone landing technology has emerged as a critical area of research, offering transformative potential across industries such as logistics, search and rescue, environmental monitoring, and autonomous transportation. This review paper provides a comprehensive analysis of vision-based systems for precise drone landings, focusing on the integration of advanced computer vision algorithms, sensor fusion, and robust control strategies. Vision-based systems, when combined with state-of-the-art sensors like GPS, IMU, and LiDAR, can significantly enhance landing accuracy, robustness, and reliability in complex scenarios. The paper reviews the challenges associated with real-time processing, including efficient object detection, tracking, and depth estimation, particularly in varying environmental conditions such as low light and cluttered surroundings. Additionally, it explores the importance of precise state estimation for ensuring safe and reliable landings. Key issues such as the integration of multiple sensor modalities, optimization of algorithms for real-time decision-making, and the development of reliable control systems to handle uncertainties and external disturbances are thoroughly examined. The paper concludes by outlining potential future research directions aimed at addressing the remaining challenges in precision landing technology, with the ultimate goal of enabling safer, more efficient, and scalable drone operations across diverse use cases.</p>