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Artificial Intelligence (AI) is revolutionizing agriculture by enhancing efficiency, productivity, and sustainability across various farming practices. AI-driven technologies, including machine learning, computer vision, and robotics, enable precision farming, allowing for real-time monitoring of crops, soil, and environmental conditions. AI algorithms are used to optimize irrigation, fertilization, and pesticide application, significantly reducing resource waste and improving crop yield. Additionally, AI-powered drones and sensors facilitate early detection of plant diseases and pests, while predictive models assist in forecasting weather patterns and market trends, aiding in strategic decision-making. Despite the promising advancements, challenges such as data availability, high costs, and the need for farmer training remain critical to the widespread adoption of AI in agriculture. This paper examines the potential of AI to transform farming practices and discusses the hurdles that need to be addressed for its broader implementation.
Choudhary et al. (Tue,) studied this question.