International Journal of Plant & Soil Science

Soil health is a critical factor for ensuring sustainable agricultural productivity and environmental balance. Over the past decade, the rapid advancement of digital tools and sensor-based technologies has revolutionised the way soil health is monitored and managed. Traditional methods, which often involved labour-intensive manual sampling and limited spatial coverage, have been gradually replaced by digital platforms and real-time sensor systems that offer precise, continuous, and scalable data collection. These innovations, ranging from IoT-based sensors, drones, and satellite imagery to advanced machine learning algorithms, are now enabling farmers, researchers, and policymakers to monitor soil conditions with unprecedented accuracy and efficiency. This review article explores the evolution of soil health monitoring tools, focusing on the integration of digital and sensor-based technologies. It examines the types of tools currently available, their applications in precision agriculture, and the challenges and limitations faced in their implementation. Additionally, the article highlights the role of artificial intelligence and machine learning in transforming data analysis and predictive modelling for soil health. Finally, the article discusses the future potential of these technologies, exploring opportunities for scaling them globally and the role of policy in supporting their widespread adoption. As digital and sensor-based tools continue to advance, they promise to play a pivotal role in achieving agricultural sustainability and improving soil management practices worldwide.