Abstract
The increasing use of drones, robotic platforms, and IoT sensors in agriculture has resulted in a growing volume of heterogeneous data that is difficult to integrate due to lack of interoperability. This paper presents three data pipelines designed within the Norwegian research project SMARAGD, targeting the transformation of siloed agritech data into interoperable NGSI-LD-compliant entities using Smart Data Models and the FIWARE framework. The pipelines cover aerial imagery, robotic imagery from ROS-based systems, and IoT sensor measurements, enriching the data with temporal and geospatial context and integrating it into a shared FIWARE-powered ecosystem. This architecture provides a foundation for decision-support tools and interoperability in land-based food production systems.