1. Characterize crops and optimize fertigation using agronomic models and ontologies:
- Study agronomic models for the prediction of evapotranspiration and process the information using a proprietary algorithm to determine water requirements.
- Research geospatial information modeling techniques from agricultural data (e.g., GIS, IoT, Copernicus) and utilize the Copernicus Land Monitoring Service (CLMS) for providing geographic information.
- Study agronomic models for fungal diseases in woody crops, highlighting the significance of plant diseases and the potential of Digital Twins and Explainable AI (XAI) in data transmission.
2. Research and design an environment based on intelligent agents and Digital Twins for crop monitoring, simulating the evolution of the phenotype in response to internal and external agents, and controlling fertigation using low-power wireless technologies:
- Research information fusion techniques from heterogeneous data sources for subsequent storage and processing using open-source, batch, and streaming-based Big Data technologies.
- Research and design a network for monitoring and controlling smart agriculture scenarios using energy and radio spectrum-efficient wireless transmission technologies.
- Investigate and design an environment based on Virtual Agent Organizations and Digital Twins for simulating the interaction of different entities in agricultural settings.
3. Investigate models based on Explainable AI (XAI) for predicting evapotranspiration, yield, and fungal diseases and cognitive systems for optimizing fertigation:
- Design crop evapotranspiration predictions from IoT and satellite imaging and investigate models based on explainable RNNs for predicting evapotranspiration and crop water balance from IoT data and multispectral imagery.
- Research and design Explainable Ensemble Learning models for predicting yields of woody crops as a function of fertigation and weather conditions.
- Research and design a cognitive system aimed at autonomous decision-making for optimizing fertigation and phytosanitary applications in woody crops.
4. Test and validate models in a small-scale environment.