- Title
- The role of big data analytics in industrial internet of things
- Creator
- Rehman, Muhammad; Yaqoob, Ibrar; Salah, Khaled; Imran, Muhammad; Jayaraman, Prem; Perera, Charith
- Date
- 2019
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/183102
- Identifier
- vital:16256
- Identifier
-
https://doi.org/10.1016/j.future.2019.04.020
- Identifier
- ISBN:0167-739X (ISSN)
- 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. © 2019 Elsevier B.V.
- Publisher
- Elsevier B.V.
- Relation
- Future Generation Computer Systems Vol. 99, no. (2019), p. 247-259
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright © 2019 Elsevier B.V.
- Rights
- Open Access
- Subject
- 4604 Cybersecurity and Privacy; 4606 Distributed Computing and Systems Software; Analytics; Big data; Cloud computing; Cyber-physical systems; Internet of Things
- Full Text
- Reviewed
- Funder
- Muhammad Imran’s work is supported by the Deanship of Scientific Research at King Saud University, Saudi Arabia through Research group No. ( RG # 1435-051 ).
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