Optimizing Olive Harvesting Efficiency Through UAVs and AI Integration

Haider Ali Khan, Sajjad Ali Rao and Umar Farooq

Journal of Agricultural Science, 2024, vol. 16, issue 11, 45

Abstract: Olive harvesting, integral to global agriculture, faces challenges with traditional gathering methods which are labor-intensive and limited in precision, highlighting the need for innovative approaches. The study explores the application of Unmanned Aerial Vehicles (UAVs) in olive harvesting, with the aim to enhance efficiency and sustainability. Traditional methods, employing wood rakes, sticks, and rudimentary mechanical devices, pose challenges with high labor intensity and potential tree damage. UAVs present a transformative solution, offering aerial surveying, high-resolution imaging, and harvest timing data collection. This study evaluates existing olive harvest technologies, illuminating the superior efficiency of UAVs in minimizing damage and maximizing yield. The Potohar region in Pakistan exemplifies one area of intensive olive production, emphasizing the need for precision Agri-techniques. This study introduces the conceptual design of olive harvesting using drones, demonstrating its potential to revolutionize traditional practices, provide real-time monitoring, and enhance environmental sustainability. Results indicate substantial reductions in non-harvestable fruit and wood damage with drone-based harvesting, underscoring its promise for increased yield and reduced environmental damage. In conclusion, this study advocates for the adoption of precision agriculture techniques, integrating Artificial Intelligence and aerial technologies, to propel the olive industry's productivity and environmental impact forward.

Date: 2024
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