Leveraging fog computing for sustainable smart farming using distributed simulation

The concept of smart farming has led to the use of technology to enhance agricultural productivity. With access to low-cost sensors and management systems, more farmers are adopting this technology to achieve sustainable growth. However, in literature, there are no simulation platforms to help researchers and users understand sensor deployment, and data collection and processing. In this article, we propose a framework designed to provide a complete farming ecosystem. The toolkit facilitates users to simulate custom farming scenarios, specifically to identify sensor placement, coverage area, line-of-sight deployment, and data gathering through the relay mechanism or airborne systems, mobility models for mobile nodes, energy models for on-ground sensors and airborne vehicles, and backend computing support using the fog computing paradigm. Furthermore, in most of the existing works, network parameters are ignored, which can impact the overall performance of any deployed system. Therefore, the proposed framework also provides a benchmark in terms of transmission delay, packet delivery ratio, energy consumption, and system resources usage.