From Sensors to Insights: A Review of IoT Applications in Soil Health Monitoring and Precision Farming

Abstract

Soil health is a prerequisite for agricultural sustainability; however, the decline of soil health is a global crisis. Although conventional soil health analyses, reliant on laboratory methods, are reliable they are not time efficient, resource efficient and practical in terms of being timely for on-farm decision making. At the same time as the global food demand increases, resources become more limited, and climate change is necessitating an implementation of new technologies to monitor soil health in a continuous and scalable fashion. The Internet of Things (IoT) offers the opportunity to move to a new paradigm using low power sensors, wireless communication, cloud computing, and machine learning for agricultural applications. This synthesis will provide a summary of the state of soil health monitoring in reference to IoT applications. We will provide a brief overview of agronomically relevant indicators of soil health (physical, chemical and biological) of soil health and consider pertinent sensing technologies that will facilitate in situ measurement of these indicators and systems architecture as pertaining to IoT systems engineering / protocols and cloud computing will be evaluated for use in differing agricultural contexts (i.e., large scale commodity agriculture, smallholder, etc.). The farm case studies examined from cases around the globe serve as an applied representation of how IoT initiatives can lead to savings in water, nutrient use efficiency, and/or yield improvements. Although successful, the case studies are not without challenges associated with sensor drift, communications delays, power capabilities of sensors and sensors as equipment cost, and farmers willingness to adopt. This synthesis will conclude with some future directions of edge artificial intelligence, block chain enabled data fidelity, and digital twins (models) for agricultural environments in real time context.