An Ontology-Driven Solution for Capturing Spatial and Temporal Dynamics in Smart Agriculture

Semantic web technologies have been frequently used in smart agriculture systems to address integration and interoperability issues, while enhancing expressiveness through their automatic reasoning capabilities. Despite continuous advancements in the field, there is no existent ontology capable of providing a comprehensive representation of the spatial and temporal knowledge, essential in the context of smart farming. In this paper we propose such a model, pass it through a rigorous validation and verification process, and employ it as a representational layer in an IoT agricultural application. The resulting system utilizes real-world high-quality information to offer various functionalities, including crop health monitoring and disease risk forecasting. This work opens a new perspective regarding the development of smart farming applications, by enabling ontological models to fully exploit the spatial and temporal dimensions of agricultural information.