The Role of Big Data Analytics in Industrial Internet of Things
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Abstract (arXiv)
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 as future research directions as well.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Apr 2019.
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Citing papers per year: 2021: 2; 2022: 3; 2023: 0; 2024: 0; 2025: 0; 2026: 1.
6 papers.
- 2021Fusion of Federated Learning and Industrial Internet of Things: A Surveycited by 28
- 2021The Duo of Artificial Intelligence and Big Data for Industry 4.0: Review of Applications, Techniques, Challenges, and Future Research Directionscited by 3
- 2022Query-based Industrial Analytics over Knowledge Graphs with Ontology Reshapingcited by 0
- 2022From Traditional Adaptive Data Caching to Adaptive Context Caching: A Surveycited by 0
- 2022Reinforcement Learning Based Approaches to Adaptive Context Caching in Distributed Context Management Systemscited by 0
- 2026Internet of Everything in the 6G Era: Paradigms, Enablers, Potentials and Future Directionscited by 0
- 2026Internet of Everything in the 6G Era: Paradigms, Enablers, Potentials and Future Directions27 Apr 2026
- 2022Reinforcement Learning Based Approaches to Adaptive Context Caching in Distributed Context Management Systems22 Dec 2022
- 2022From Traditional Adaptive Data Caching to Adaptive Context Caching: A Survey21 Nov 2022
- 2022Query-based Industrial Analytics over Knowledge Graphs with Ontology Reshaping22 Sep 2022
- 2021The Duo of Artificial Intelligence and Big Data for Industry 4.0: Review of Applications, Techniques, Challenges, and Future Research Directions6 Apr 2021
- 2021Fusion of Federated Learning and Industrial Internet of Things: A Survey4 Jan 2021