A Context-Aware Middleware Cloud Approach for Integrating Precision Farming Facilities into the IoT toward Agriculture 4.0

Eleni Symeonaki,Konstantinos Arvanitis,Dimitrios Piromalis

doi:10.3390/app10030813

Eleni Symeonaki, Konstantinos Arvanitis + Show 1 more

Open Access

https://doi.org/10.3390/app10030813

Copy DOI

Abstract

The adoption of Precision Farming (PF) practices involving ubiquitous computing advancements and conceptual innovations of “smart” agricultural production toward Agriculture 4.0 is a significant factor for the benefit of sustainable growth. In this context, the dynamic integration of PF facility systems into the Internet of Things (IoT) represents an excessive challenge considering the large amount of heterogeneous raw data acquired in agricultural environments by Wireless Sensor and Actuator Networks (WSANs). This paper focuses on the issue of facilitating the management, process, and exchange of the numerous and diverse data points generated in multiple PF environments by introducing a framework of a cloud-based context-aware middleware solution as part of a responsive, adaptive, and service-oriented IoT integrated system. More particularly, the paper presents in detail a layered hierarchical structure according to which all functional elements of the system cope with context, while the context awareness operation is accomplished into a cloud-based distributed middleware component that is the core of the entire system acting as a Decision Support System (DSS). Furthermore, as proof of concept, the functionality of the proposed system is studied in real conditions where some evaluation results regarding its performance are quoted.

Highlights

Agriculture is undeniably one of the major sectors of primary industry which, according to the United Nations Food and Agriculture Organization (FAO), has to address the challenge of raising its productivity by up to 60% during the 21st century to provide sufficient food supply for the increasing world population [1]
Testing the system on two application scenarios allowed its proper analysis and evaluation in terms of health, operation, and performance, whereas considerable attention was given to the validation of the response time parameter, in terms of the real-time constraint
At first it has been verified that raw data were being suitably acquired, transferred, stored and managed in the Microsoft Azure cloud platform to retrieve the relevant information as illustrated in Screenshotofofnodes nodesas aspresented presentedin inthe theMicrosoft

Summary

Introduction

Agriculture is undeniably one of the major sectors of primary industry which, according to the United Nations Food and Agriculture Organization (FAO), has to address the challenge of raising its productivity by up to 60% during the 21st century to provide sufficient food supply for the increasing world population [1]. This aim must be achieved taking into account the imperative necessity of using natural resources according to sustainable strategies due to the escalating pressures on ecosystems, biodiversity, lands, and water.

Objectives

Results

Discussion

Conclusion