Scalable Architecture and Intelligent Edge with 5G-Advanced, MEC, IoT, UAVs and AI for a Sustainable Agriculture and Food Operations

Abstract

Efficient agricultural production increasingly relies on advanced technologies to address the challenges of sustainability, scalability, and cost-effectiveness. This paper investigates the application of 5G-Advanced networks as a transformative enabler for modern agriculture, offering significant efficiency and cost advantages over traditional wireless sensor networks. By leveraging cutting-edge technologies such as IoT, Multi-access Edge Computing, and Artificial Intelligence/Machine Learning/Deep Learning, this applied research study introduces an innovative framework that shifts actuation decisions from user equipment to the edge, enhancing scalability and simplifying device design. The proposed framework integrates drone-supported intelligent robotics with IoT-driven edge computing, tailored to the unique demands of rural agricultural areas. Case studies from an award-winning TM-Forum catalyst project validate the framework’s efficacy in architecture modeling, focusing on drone-assisted 5G networks, advanced orchestration, network slicing, and ultralow-latency communication. These case studies emphasize precision and scalability in critical agricultural operations such as weeding, irrigation, harvesting, crop, animal and storage monitoring. The findings underscore the potential of 5G-Advanced networks to revolutionize agriculture by enabling precise, efficient, and sustainable practices. This approach addresses diverse system requirements and offers a robust solution for future-ready agricultural technologies, paving the way for a scalable and resilient agricultural ecosystem.