Abstract
This technical article comprehensively explores the integration of Artificial Intelligence in agricultural systems, with a primary focus on precision farming methodologies and their practical implementation. It conducts an in-depth examination of the technological framework underpinning agricultural AI systems, encompassing sophisticated data acquisition infrastructure and advanced machine learning implementations. Through detailed analysis, the article investigates the critical technical components of precision farming systems, emphasizing the integration of sensor technologies spanning both aerial and ground-based platforms, alongside robust data analytics architectures. It systematically addresses the prevalent challenges in agricultural data integration and system scalability, presenting innovative solutions for these complex issues. Furthermore, the article explores emerging technological developments in the field, including cutting-edge sensing technologies and AI algorithm enhancements, offering valuable insights into future trajectories of agricultural AI applications. The comprehensive article illuminates how AI technologies are fundamentally transforming traditional farming practices through the implementation of sophisticated automated decision-making processes and enhanced resource management capabilities, ultimately contributing to more efficient and sustainable agricultural operations
Published Version
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