We propose a drone-based AI-driven framework for densely fruited crop detection, yield estimation, and ripeness analysis, integrating explainable agriculture solutions. In the first step, our system detects crops using advanced computer vision techniques. This is followed by precise yield estimation and ripeness assessment using deep learning models. To enhance transparency and decision-making, we incorporate an explainable AI solution powered by large language models (LLMs), providing insights into model predictions and enabling informed agricultural practices. Our approach aims to optimize precision farming by leveraging autonomous drones and AI-driven analytics for enhanced productivity and sustainability.
#AgriRobotics #Drones #dronesforagriculture #KUCAR #PCIR #DrIfanHussainLab #ModrenAgriculture #agriculturaltechnology #agriculturalmachinery
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