A platform to support the fast development of digital twins for agricultural holdings

Industry 4.0 has advanced in agriculture through Smart Agriculture initiatives, yet open-field farming lags in the adoption of digital twins. Although digital twins have transformed manufacturing since 2011, their application in open-field farming remains limited by environmental variability, data scarcity, and financial constraints. This paper addresses four gaps: the lack of affordable platforms for small farms that dominate European agriculture; the need to manage agricultural complexity through data-driven models rather than the physical modelling approaches prevalent in non-agricultural sectors; the absence of open sources solutions adapted to agriculture’s slower innovation pace; the breach between technology and farmers. The platform features innovations in data workflow integration, open data incorporation, a cost-effective shared warehouse, and scalable data pipelines. To validate the proposed platform, a case study with two example digital twins mirroring two fields is conducted. This implementation ran efficiently on modest hardware (2 vCPUs, 4GB RAM). It achieved an average CPU usage of 60%, RAM usage of 2.5 GB, and a deployment time of around one minute. This helps lowering adoption barriers for small holdings and bridging the gap between basic monitoring and complex future systems. • Global shared state enhances data integration, reducing redundancy. • Digital twin inter-communication improves AI models and asset feedback. • Flexible modular design enables seamless farming system communication. • Autonomous open-source platform automates data collection and analysis. • Real implementation demonstrated using dual digital twin prototypes.