Aril 28, 2023 | JOURNAL OF BIG DATA
Researchers from Spain have developed an innovative system for managing spatial, temporal, and semantic data in precision agriculture within the realm of the Internet of Things (IoT). This system addresses the challenges posed by the diverse data collected from sensors deployed on farms and the lack of standards, which hampers interoperability with other management solutions. The proposed solution includes a data query system that enables farmers and users to resolve daily queries, aiding in decision-making, monitoring, and task automation. The framework ensures service interoperability and has been validated with two European smart farming platforms, AFarCloud and DEMETER. To evaluate the system, a neural network was implemented and trained using the framework, providing accurate forecasts for crop harvest and baling, particularly for forage legume crops used in livestock feeding. The study demonstrates the system's high performance in handling complex spatio-temporal semantic queries, and concludes with a distributed framework that integrates external agricultural data models to enable effective management of such data in precision agriculture.
Graphical abstract
