Ines Neji

This research project centers on the development of an AI-powered Digital Twin framework to advance precision agriculture and promote sustainable farm management. By leveraging cutting-edge machine learning techniques in conjunction with imaging and environmental data, the project seeks to build intelligent models for real-time crop monitoring, early disease detection, and efficient resource optimization. The framework integrates live field inputs with dynamic virtual simulations, enabling proactive, data-informed decision-making for farmers and agricultural stakeholders. Conducted in partnership with the University of Konstanz, the initiative combines on-site experimentation with remote system development and encompasses the design, validation, and deployment of a fully functional Digital Twin prototype. The project is poised to significantly contribute to the digital transformation of agriculture by delivering forward-looking solutions to contemporary farming challenges and bridging the gap between physical farm environments and their intelligent digital counterparts.