Cloud-Fog-Edge Computing in Smart Agriculture in the Era of Drones: a systematic survey

Abstract

In the current era of agricultural robotization, it is necessary to use a suitable automated data collection system for a constant plant, animal and machine monitoring. In this context, Cloud Computing (CC) is a well-established paradigm for building service-centric farming applications. However, the huge amount of data has put an important burden on data centers and network bandwidth and pointed out issues that cloud-based applications face such as large latency, bottlenecks because of central processing, compromised security, and lack of offline processing. Fog Computing (FC) and Edge Computing (EC) are gaining exponential attention and becoming attractive solutions to bring CC processes within reach of users and address computation-intensive offloading and latency issues. These paradigms from Cloud to Edge computing are already forming a unique ecosystem with different architectures, storage, and processing capabilities. The heterogeneity of this ecosystem comes with certain limitations and challenges. This paper carries out a systematic review of the latest high-quality literatures and aims to identify similarities, differences and the main use cases in the mentioned paradigms particularly when using Unmanned Aerial Vehicles (UAVs).