Abstract: On one hand, the emergence of cutting-edge technologies like AI, Cloud Computing, and IoT holds immense potential in Smart Farming and Precision Agriculture. These technologies enable real-time data collection, including high-resolution crop imagery, using Unmanned Aerial Vehicles (UAVs). Leveraging these advancements can revolutionize agriculture by facilitating faster decision-making, cost reduction, and increased yields. Such progress aligns with precision agriculture principles, optimizing practices for the right locations, times, and quantities. On the other hand, integrating UAVs in Smart Farming faces obstacles related to technology selection and deployment, particularly in data acquisition and image processing. The relative novelty of UAV utilization in Precision Agriculture contributes to the lack of standardized workflows. Consequently, the widespread adoption and implementation of UAV technologies in farming practices are hindered. This paper addresses these challenges by conducting a comprehensive review of recent UAV applications in Precision Agriculture. It explores common applications, UAV types, data acquisition techniques, and image processing methods to provide a clear understanding of each technology’s advantages and limitations. By gaining insights into the advantages and challenges associated with UAV-based applications in Precision Agriculture, this study aims to contribute to the development of standardized workflows and improve the adoption of UAV technologies.

El Mehdi Raouhi, Mohamed Lachgar, Hamid Hrimech and Ali Kartit, “Unmanned Aerial Vehicle-based Applications in Smart Farming: A Systematic Review” International Journal of Advanced Computer Science and Applications(IJACSA), 14(6), 2023. http://dx.doi.org/10.14569/IJACSA.2023.01406123

@article{Raouhi2023,
title = {Unmanned Aerial Vehicle-based Applications in Smart Farming: A Systematic Review},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.01406123},
url = {http://dx.doi.org/10.14569/IJACSA.2023.01406123},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {6},
author = {El Mehdi Raouhi and Mohamed Lachgar and Hamid Hrimech and Ali Kartit}
}