Using ubiquitous computing technology to realise scalable intelligent agricultural environments

Wireless networks allow the deployment of sensing systems and actuation mechanisms at a much finer level of granularity than has been possible before. This paper is focused on connecting sensor data with actuators through a decision-making layer with learning capability. The decision making process regarding the provision of agricultural resources is extended this by on-line monitoring significant plant and environmental parameters and by applying machine-learning algorithms for inducing rules by analysing logged datasets to determine the significant thresholds of plant-based parameters.