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.
| Original language | English |
|---|---|
| Pages (from-to) | 247-259 |
| Number of pages | 13 |
| Journal | Future Generation Computer Systems |
| Volume | 99 |
| DOIs | |
| Publication status | Published - 29 Apr 2019 |
| Externally published | Yes |
Keywords
- Analytics
- Big data
- Cloud computing
- Cyber-physical systems
- Internet of Things
ASJC Scopus subject areas
- Software
- Hardware and Architecture
- Computer Networks and Communications
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