Abstract
Precision agriculture leverages data science and technology to optimize farming practices, enhance crop yields, and promote sustainability. This review examines how data-driven approaches are revolutionizing agriculture through improved decision-making, resource efficiency, and environmental stewardship. Key technologies enabling precision agriculture are discussed, including remote sensing, IoT sensors, AI/machine learning, and farm management information systems. The paper explores applications such as variable rate technology, yield mapping, and predictive analytics. Challenges related to data management, interoperability, and adoption barriers are analyzed. The review concludes that precision agriculture, powered by data science, offers significant potential to address food security and sustainability challenges, but requires continued research and interdisciplinary collaboration to realize its full benefits.
Published Version
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