Digital and data driven agriculture and food systems
- Development of crop yield prediction models using Machine Learning (ML) and Internet of Agro-Things (IoATs) using multisource data (multi-source data such as climate reanalysis data, satellite imagery data, weather data, soil data, and proximal IoT data)
- Development of AI driven farm monitoring and management systems that can collect information of farmers, perform data analytics and
- Investigating platforms for smart decision-making to tackle climate change, agriculture and food production systems in Africa (e.g., Climate tech platform to mitigate climate risks, satellite and AI/ML based solutions, sustainable sourcing and traceability solutions using blockchain, farmer advisory, prediction and forecasting tools, soil organic carbon monitoring and regenerative Agri solutions).
- Digital Farming – investigating solutions for digital record of farmers, farmland, & monitor the value chain centrally and generate customized reports