Enhancing agricultural meteorology: Qualified data production through an interoperable cyber–physical system

This work aimed at developing an interoperable, geospatial and modular Cyber-Physical System (CPS), called AgriMetSupport, designed to effectively manage sensor networks, weather stations, and agrometeorological data across heterogeneous territories, facilitating advanced territorial and integrated risk management. AgriMetSupport integrates processing modules, including quality control, gap-filling, spatial interpolation, and gridded data-cube management. A validation procedure was executed in a proposed case study through perturbation of agrometeorological data, allowing direct assessment of the system’s capability in anomaly detection and gap-filling under controlled noise conditions. The validation demonstrated high robustness of AgriMetSupport, achieving over 90% accuracy in automated anomaly detection and a low error (cross-validation RMSE < 1 °C, and ground-truth mean absolute error 1.13 °C) in gap-filled air temperature data. The CPS proved effective in simultaneously managing multiple sensor networks, producing qualified and certified data continuously and in real-time. AgriMetSupport significantly enhances agricultural meteorology by standardizing data quality procedures and enabling geospatial integration. Its flexible architecture can manage federated sensor networks efficiently, promoting better-informed agricultural decisions, supporting territorial planning, and strengthening downstream scientific and technological applications. • AgriMetSupport is a modular CPS for managing agrometeorological sensor networks. • WeatherProg automates data validation, gap-filling, and geospatial interpolation. • Robust quality control and gap-filling ensure high-accuracy, certified data. • Perturbation-based validation shows > 90% anomaly detection and low infill error. • The scalable CPS supports federated networks and downstream scientific services.