PHÁT TRIỂN HỆ THỐNG GIÁM SÁT CHẤT LƯỢNG RAU HỌ CẢI ỨNG DỤNG IoT VÀ AI

Tóm tắt

Cruciferous vegetables play an essential role in Vietnamese agriculture, providing vital nutrients for consumers and contributing significantly to the agricultural economy. However, traditional methods for monitoring crop quality and detecting diseases remain limited in both accuracy and efficiency. This study proposes a comprehensive monitoring system that integrates Internet of Things (IoT) and Artificial Intelligence (AI) technologies to track environmental conditions and detect diseases in cruciferous crops. The system employs Node.js for the backend, ReactJS and React Native for user interfaces, and MongoDB for data storage using the bucket pattern and vector database models. Notably, two parallel AI architectures are implemented: the YOLO model for automatic disease detection from periodic images, and a Retrieval-Augmented Generation (RAG) framework combined with VGG16 for providing detailed crop condition analysis. Experimental results on 100 samples achieved 90% accuracy, demonstrating the system’s effectiveness. This research offers a practical solution to help farmers accurately monitor environmental conditions, detect diseases early, and make timely cultivation decisions, while also enhancing transparency for consumers regarding the origin and quality of agricultural products.