Artificial intelligence of things (AIoT) for precision agriculture: applications in smart irrigation, nutrient and disease management
Jalal Bayar, Nawab Ali, Zhichao Cao, Yidong Ren, Younsuk Dong
Abstract
Despite the growing global demand for efficient and sustainable agricultural practices, many traditional farming systems still rely on manual decision-making, which can be inefficient and resource intensive. This review comprehensively examines the applications of Artificial Intelligence of Things (AIoT) in three critical domains of precision agriculture, such as smart irrigation, nutrients and disease management. Through the deployment of interconnected sensor networks, edge and cloud computing platforms, and AI algorithms, AIoT systems facilitate site-specific monitoring and control key environmental and crop parameters. In irrigation, AIoT empowers farmers to optimize water distribution through real-time soil moisture sensing, predictive analytics and dynamic irrigation scheduling. Precision nutrient management utilizes unmanned aerial aehicles , soil sensors, and AI-powered data analysis to monitor nutrient availability and inform optimized fertilization strategies, thereby improving nutrients efficiency and reducing environmental degradation. Similarly, AIoT in disease management enhances surveillance and predictive capabilities by integrating sensor data with AI models to early detect abiotic stresses, enabling timely and targeted interventions. Although the significant benefits of AIoT, its implementation faces several challenges. These include high setup costs, data connectivity issues in rural areas, inconsistent sensor reliability, cybersecurity risks, and limited scalability for smallholder farming systems. Additionally, gaps in technical knowledge and infrastructure pose barriers to widespread adoption. However, advancements in 5G technology, edge computing, and sensor miniaturization offer promising avenues for scaling AIoT in agriculture. This review therefore highlights the transformative potential of AIoT in improving climate-smart and sustainable agriculture by converting data into actionable insights to enhance resilience and food security.