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. 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 bestpractices 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 work presents a narrative of the most recent developments in the use of AI in agricultural farming across a range of domains in Nigeria. This was done by reviewing and identifying the AI methodological approach used in allied research carried out for crop management. Appraisal of the researches, AI technique employed, contributions and milestones in this domain, amassed in the literature reveals plethora of obstacles encompassing restricted data accessibility, interpretability of models, and implementation inresource-constrained settings amongst others. It is therefore recommended that critical attention be given to address these restrictions so as to expand the potential of AI-driven solutions and attaining precision agriculture's full promise for global food security.