Internet of Things (IoT) Application Model for Smart Farming

TL;DR

This paper proposes a distributed data flow model for smart farming using IoT, evaluating cloud and fog deployment strategies to optimize latency and network usage.

Contribution

It introduces a novel distributed data flow model for IoT-based smart farming and compares cloud and fog deployment strategies.

Findings

Fog-based deployment reduces end-to-end latency.

Cloud-based deployment has higher network usage.

Model enhances real-time decision-making in smart farming.

Abstract

Smart Farming has brought a major transformation in the agriculture process by using the Internet of Things (IoT) devices, emerging technologies such as cloud computing, fog computing, and data analytics. It allows farmers to have real-time awareness of the farm and help them make smart and informed decisions. In this paper, we propose a distributed data flow (DDF) based model for the smart farming application that is composed of interdependent modules. We evaluate the proposed application model using two deployment strategies: cloud-based, and fog-based where the application modules are deployed on the fog and the cloud data center respectively. We compare the cloud-based and fog-based strategy in terms of end-to-end latency and network usage.