AI-Driven Precision Agriculture: A Narrative of the Potential for Sustainable Crop Management

Abstract

In precision agriculture, artificial intelligence (AI) has become a game-changing technology that allows farmers to maximize crop management and boost output. Recently, developments in machine learning and AI have opened up new opportunities for precision agriculture, particularly in the field of crop management. Precision farming is made possible by AI-powered systems that provide data-driven insights. Early disease identification is made possible by computer vision and machine learning techniques, which also enable tailored interventions to reduce yield losses. Farmers can receive personalized advice on the best practices for planting, irrigation, and fertilizer management via chatbots and advisory services powered by AI. Artificial intelligence algorithms combined with sensor networks allow for just-in-time decision making by providing real-time weather, plant health, and soil monitoring. Despite the well-established advantages of AI in precision agriculture, there are still difficulties which calls for continual research. This review examines the most recent developments in the use of AI in agricultural farming across a range of domains. Obstacles encompass restricted data accessibility, interpretability of models, and implementation in resource-constrained settings. Addressing these restrictions is critical to expanding AI-driven solutions and attaining precision agriculture's full promise for global food security.