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The role of big data analytics in industrial Internet of Things

Swinburne Research Bank (Swinburne University of Technology)Published 1 January 2019
Muhammad Habib ur Rehman, Ibrar Yaqoob, Khaled Salah, Muhammad Imran, Prem Prakash Jayaraman, Charith Perera
Citations356

TL;DR

This study investigates the recent BDA technologies, algorithms and techniques that can lead to the development of intelligent IIoT systems and devise a taxonomy by classifying and categorising the literature on the basis of important parameters.

Abstract

Big data production in industrial Internet of Things (IIoT) is evident due to the massive deployment of sensors and Internet of Things (IoT) devices. However, big data processing is challenging due to limited computational, networking and storage resources at IoT device-end. Big data analytics (BDA) is expected to provide operational- and customer-level intelligence in IIoT systems. Although numerous studies on IIoT and BDA exist, only a few studies have explored the convergence of the two paradigms. In this study, we investigate the recent BDA technologies, algorithms and techniques that can lead to the development of intelligent IIoT systems. We devise a taxonomy by classifying and categorising the literature on the basis of important parameters (e.g. data sources, analytics tools, analytics techniques, requirements, industrial analytics applications and analytics types). We present the frameworks and case studies of the various enterprises that have benefited from BDA. We also enumerate the considerable opportunities introduced by BDA in IIoT. We identify and discuss the indispensable challenges that remain to be addressed, serving as future research directions.

Keywords

Computer ScienceBusiness, Management and AccountingEngineering