American International Journal of Research and Innovation

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Volume 8 Issue 5
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Artificial Intelligence Applications in Precision Farming Systems

Author(s) Davide Cammarano
Country Denmark
Abstract The integration of artificial intelligence (AI) into precision farming systems has introduced significant advancements in agricultural productivity, resource optimization, and sustainable farm management. Modern agriculture increasingly relies on intelligent technologies capable of analysing complex environmental, crop, and operational data to support accurate decision-making. Artificial intelligence applications, including machine learning, computer vision, predictive analytics, and autonomous systems, provide advanced capabilities for crop monitoring, disease identification, yield prediction, irrigation management, and agricultural automation. This conceptual research article examines the role of artificial intelligence applications in precision farming systems by analysing technological frameworks, agricultural benefits, implementation challenges, and future development opportunities.
The study adopts a conceptual research methodology based on the synthesis of scholarly literature, precision agriculture models, AI-based farming approaches, and digital agriculture frameworks. The analysis indicates that AI technologies enhance farming efficiency by enabling real-time monitoring, predictive decision-making, and optimized resource utilization. However, challenges related to data availability, technological affordability, digital infrastructure, algorithm reliability, and farmer adoption remain significant barriers. The study concludes that AI-enabled precision farming can contribute substantially to sustainable agricultural development when supported by appropriate infrastructure, farmer training, responsible data management, and inclusive technology adoption strategies.
Keywords Artificial Intelligence; Precision Farming; Machine Learning; Smart Agriculture; Computer Vision; Predictive Analytics; Agricultural Automation
Field Engineering
Published In Volume 7, Issue 5, September-October 2025
Published On 2025-09-14
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