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Modern agriculture faces immense challenges, from climate change to the urgent need for more sustainable practices. Smart Droplets recognises and addresses these challenges by combining digital twins with artificial intelligence to guide farmers toward more resilient practices. A “digital twin” is a virtual representation of a physical system, like a crop field, that is kept in sync with its real-world counterpart through data assimilation. This virtual copy can run simulations and test scenarios without real-world risk. Smart Droplets harness these digital twins to optimize nutrient management, improve crop health, and adapt to changing conditions in real time. Paired with reinforcement learning (RL), a type of AI where agents learn optimal policies through trial and error, Smart Droplets transform digital twins into a powerful decision support system for sustainable farming.
A new paper from Smart Droplets partners from Wageningen University & Research and VizLore LLC in Smart Agricultural Technology details a practical system that integrates these technologies to revolutionize how farmers manage resources like pesticides and fertilizers.
1. The Training Ground (Phase 1)
Before deployment, the AI agent undergoes intensive offline training in a simulated environment. This environment uses established agricultural models, specifically the WOFOST crop growth model and the A-scab plant disease model, to replicate farm conditions. The AI agent interacts with the simulation, and when its actions lead to desirable outcomes like high yield with minimal chemical use, it receives a “reward”. Through this trial-and-error process, it learns the best strategies for crop management.
2. The Field Assistant (Phase 2)
Once trained, the AI is deployed in the field where it is connected to the farm’s digital twin. The digital twin provides the AI with the current state of the crop, which it analyzes to generate optimized recommendations for the farmer. A key feature of the architecture is its interoperability, achieved using the FIWARE framework and NGSI-LD standard to ensure seamless communication between diverse sensors, software, and machinery.
The system was tested in two real-world pilot studies during the 2025 growing season.
This research provides a blueprint for a more precise and sustainable future for agriculture. The system’s modular and model-agnostic design means it can be adapted for different crops and management tasks, such as irrigation. This integration of digital twins and AI points towards a farming future that is more efficient, productive, and environmentally friendly. While challenges such as data collection costs and farmer adoption remain, the pathway is clear: smart, adaptive tools like Smart Droplets can help agriculture meet sustainability goals while safeguarding yields.
Read the full paper in Smart Agricultural Technology to explore the details of how Smart Droplets and its partners are transforming farming practices. (link)
