From field to data: A global review of precision agriculture for smart and sustainable farming systems

Abstract

Precision agriculture (PA) utilizes advanced technological systems to enhance crop productivity and farm efficiency while minimizing negative ecological consequences. Contemporary agricultural challenges, including weeds, plant diseases, pest infestations, inefficient irrigation and soil management, and suboptimal crop practices, have resulted in significant yield losses and negative environmental impacts. These issues are compounded by the rising global demand for food, driven by population growth, and the finite availability of arable land. Addressing these complex problems requires innovative and adaptive solutions. PA offers a viable pathway forward, leveraging its core strengths of flexibility, accuracy, cost-efficiency, and enhanced operational effectiveness to transform production systems. In this article, we examined the convergence of advanced technological systems, such as artificial intelligence (AI), the Internet of Things (IoT), variable-rate application technologies, remote sensing, and Geographic Information Systems (GIS), to tackle the pressing agricultural constraints imposed by shrinking natural resources and rising global population demands. Additionally, we provided a review of the contemporary status of PA, encompassing recent technological advancements in unmanned aerial systems (drones), sensor networks, and machine learning (ML) applications. The scope for future innovation in this domain is extensive, heralding a transformative phase in agriculture characterized by heightened efficiency and sustainability, which is critical for ensuring global food security.

Keywords

precision farming / big data / artificial intelligence models / innovative and adaptive solutions / pest and disease management / weeds monitoring

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