A Fog Computing-based IoT Framework for Precision Agriculture

Abstract

The challenge of analyzing and processing a huge amount of data is becoming increasingly important in this fourth industrial revolution era. In this scenario, Cloud Computing and Internet of Things (IoT) allow to build up an interconnected network of smart things. These two paradigms do not allow solving the Computing problems yet. Fog Computing aims at moving the processing abilities closer to the end users, avoiding an excessive exploitation of Cloud resources, further reducing computational loads. In this work, we propose a Fog-based IoT framework, which exploits the two-tier Fog and their resources, reducing the transmitted data to the Cloud, improving the computational load balancing and reducing the waiting times. The proposed Fog Computing approach is applied to the emerging area of precision agriculture, including all the techniques of agricultural land management. Furthermore, based on this framework, we have simulated and highlighted how the two-tier Fog Computing approach is able to reduce significantly the amount of transmitted data to the Cloud. We also propose and describe an application prototype, based on the previous framework, able to manage and monitor farmland, with a strong impact on both the business and environmental performance.