Revolutionizing Crop Production Through a Smart Agricultural Portal

This research presents the design and implementation of a Smart Agricultural Portal, an integrated digital ecosystem developed to improve efficiency, transparency, and sustainability across Sri Lanka’s crop production chain. The system consolidates four intelligent modules — Crop Recommendation and Resource Optimization, Early Crop Disease Detection, Automated Vegetable Grading with Marketplace Transparency, and Agricultural Workforce Management — each powered by Machine Learning and Deep Learning algorithms. The Crop Recommendation System applies ML models to optimize crop selection and resource allocation using soil and climate data. The Disease Detection module uses EfficientNet-based deep learning to identify plant pathologies from leaf imagery, enabling early intervention. The Vegetable Grading System employs YOLOv5 object detection for automated quality assessment, ensuring transparent pricing. The Workforce Management System uses a hybrid recommendation engine to intelligently match available labor with farm requirements. The combined platform delivers a scalable, AI-driven framework that enables data-informed decision-making, improves resource efficiency, and promotes sustainability. This work demonstrates the potential of an integrated, modular approach to revolutionize smart agriculture practices in Sri Lanka.