AI-Powered Precision Agriculture for Sustainable Food Production: Enhancing Yield and Reducing Resource Use
Abstract
The global demand for food is rising, necessitating more efficient and sustainable agricultural practices. This paper presents AI-powered precision agriculture techniques that use machine learning to optimize crop yield while minimizing resource inputs like water, fertilizers, and pesticides. By integrating data from drones, soil sensors, and satellite imagery, we develop predictive models to inform crop management decisions. The results show significant improvements in yield with reduced environmental impact, demonstrating how AI can play a transformative role in advancing sustainable food production on a global scale.
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