Welcome to my publications section! Here you’ll find a curated selection of my work, including journal articles and conference papers. While this list is still short and growing, it reflects some areas I am passionate about and the research I’ve been involved in.
Efficient water management is a critical challenge for modern agriculture, particularly in the context of increasing climate variability and limited freshwater resources. This study presents a comparative field-based evaluation of two fuzzy-logic-based irrigation decision support systems for vineyard management: a Mamdani-type controller with expert-defined rules and a Takagi–Sugeno system designed to enable automated learning from ultra-local historical field data. Both systems integrate soil moisture sensing, short-term forecasting, and weather predictions to provide optimized irrigation recommendations. The evaluation combines counterfactual simulations with a bootstrap-based statistical analysis to assess water use efficiency, soil moisture control, and robustness to environmental variability. The comparison highlights distinct strengths of the two approaches, revealing trade-offs between water conservation and crop stress mitigation, and offering practical insights for the design and deployment of intelligent irrigation management solutions.
@article{silvestri2025smart,title={Smart Irrigation with Fuzzy Decision Support Systems in Trentino Vineyards},author={Silvestri, Romeo and Vecchio, Massimo and Pincheira, Miguel and Antonelli, Fabio},journal={Sensors},volume={25},number={23},pages={7188},year={2025},publisher={MDPI},}
This paper presents the development and evaluation of a Fuzzy Decision Support System for irrigation management to promote sustainable water use in precision agriculture. A Mamdani-type fuzzy logic model was designed to optimize irrigation scheduling for vineyards in the Val d’Adige region of Trentino, Italy. The system integrates expert knowledge with real-time data from tensiometers and weather stations to generate adaptive, site-specific recommendations. Bayesian optimization was used to fine-tune the membership functions of fuzzy variables, enhancing system performance. Field evaluations conducted in 2023 across multiple sectors assessed total water use, average soil moisture, and days exceeding critical moisture thresholds. Results show that the system reduced total water consumption by over 52% compared to traditional methods while maintaining soil moisture within optimal levels. These findings underscore the potential of combining fuzzy logic and IoT-based sensing to support scalable, adaptive irrigation strategies across various crops and regions.
@inproceedings{codit25,author={Silvestri, Romeo and Vecchio, Massimo and Antonelli, Fabio},booktitle={2025 11th International Conference on Control, Decision and Information Technologies (CoDIT)},title={A Fuzzy Decision Support System to Optimize Irrigation Practices in Trentino Region},pages={1-6},volume={1},year={2025},}
This paper provides valuable insights into the application of spatial interpolation techniques in smart agriculture and highlights the potential for further improvements through the integration of advanced geostatistical models. Specifically, it evaluates and compares two spatial interpolation techniques, Inverse Distance Weighting and Ordinary Kriging, for estimating soil moisture in apple orchards located in the Val di Non region of Trentino, Italy. Data were gathered from 18 tensiometer sensors deployed across the apple orchards, providing continuous soil moisture measurements over a specified time frame in 2023. The accuracy of both interpolation methods was assessed using root mean square error as the primary evaluation metric, with various validation methods employed to ensure robustness. Additionally, statistical analyses were conducted to determine the significance of differences in performance between the methods. The results indicate that Inverse Distance Weighting, despite its computational efficiency, slightly outperforms Ordinary Kriging in terms of accuracy, with statistically significant lower error values, making it a preferable choice for real-time soil moisture mapping and precision irrigation management in the region.
@inproceedings{silvestri2024comparative,title={Comparative Analysis of Soil Moisture Interpolation Techniques in Apple Orchards of Trentino Region},author={Silvestri, Romeo and Vecchio, Massimo and Pincheira, Miguel and Antonelli, Fabio},booktitle={2024 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)},pages={557--562},year={2024},organization={IEEE},}
