Article: “A Novel 5G PMN-Driven Approach for AI-Powered Irrigation and Crop Health Monitoring”
Article Link: https://ieeexplore.ieee.org/abstract/document/10662981
Student Authors:
• Nguyen Tan Tang - MMCL 2019 - Primary Author
Supervisor: Assoc. Prof. Dr. Le Trung Quan
Abstract:
Precision agriculture is a critical field for addressing food security for a growing population. This article introduces an innovative approach combining deep learning with a 5G Private Mobile Network (PMN) to create a smart agriculture system. The 5G PMN infrastructure was simulated using UERANSIM and Free5GC with Quantum Key Distribution Function (QKDF) integration. 5G connectivity enhances agricultural practices by enabling real-time monitoring of crop health and reliable transmission of irrigation control commands. Besides using 5G, our proposed system incorporates a lightweight model and three YOLOv8 models for AI-powered irrigation and crop health monitoring. The lightweight model automatically generates irrigation schedules based on real-time weather conditions and soil moisture levels, optimizing water requirements for crops. The three YOLOv8 models are trained to predict growth stages, health status, and nutritional status (nitrogen, phosphorus, and potassium). All deep learning models are optimized for lettuce crops and feature lightweight architecture for easy deployment on low-power devices. Tests on evaluation datasets demonstrate promising accuracy: the irrigation scheduling model achieves 73%, the growth stage model reaches 93.8%, the health status model attains 87%, and the nutritional status model reaches 83%. This research enhances precision agriculture by offering practical solutions for improved irrigation management and crop health monitoring. We also developed a QKDF integrated with the 5G core network, enhancing the proposed system’s security by generating secure session keys with a 256-bit length.
IEEE Access is a multidisciplinary open-access journal by the Institute of Electrical and Electronics Engineers (IEEE), established in 2013. This journal publishes high-quality research in various fields, including electronic engineering, information technology, artificial intelligence, telecommunications, computer science, and other technology sectors. With an open-access model, IEEE Access articles are freely accessible, promoting the dissemination and application of research worldwide. IEEE Access is one of the prestigious journals in engineering and technology, achieving numerous milestones over the years. According to the Journal Citation Reports (JCR) in 2023, IEEE Access has an Impact Factor of 3.9, placing it among the high-impact journals in electrical and electronic engineering. Additionally, it is classified as Q1 (quartile 1) in many scientific research areas, indicating it ranks in the top 25% of journals according to Scopus or similar assessment systems.
