International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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AI-Driven Precision Agriculture: Optimizing Crop Yield and Resource Efficiency

Author(s) Neetu Gangwani
Country United States
Abstract This article explores the multifaceted applications of Artificial Intelligence (AI) technologies in precision agriculture, focusing on their potential to significantly enhance crop yields while optimizing resource utilization. The article examines five key areas where AI is making substantial impacts: predictive
analytics for crop management, intelligent irrigation systems, automated pest and disease detection, precision fertilizer application, and robotic harvesting. By integrating data from various sources and employing advanced machine learning algorithms, these AI-driven systems demonstrate remarkable
improvements in efficiency, accuracy, and sustainability. The article highlights significant advancements, such as a 15% improvement in yield prediction accuracy, up to 30% reduction in water usage, and a 20% decrease in fertilizer use without compromising crop yields. While acknowledging challenges such as
data privacy concerns and initial investment costs, the article underscores the long-term benefits of AI adoption in agriculture, including increased profitability, environmental sustainability, and improved food security. This comprehensive analysis provides insights into how AI-driven precision agriculture is
reshaping modern farming practices and its potential to address global food production challenges while reducing agriculture's environmental footprint.
Keywords Keywords:Precision Agriculture, Artificial Intelligence, Crop Yield Optimization, Resource Efficiency, Sustainable Farming
Field Computer
Published In Volume 6, Issue 6, November-December 2024
Published On 2024-11-05
Cite This AI-Driven Precision Agriculture: Optimizing Crop Yield and Resource Efficiency - Neetu Gangwani - IJFMR Volume 6, Issue 6, November-December 2024.
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E-ISSN 2582-2160
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