Abstract
Industry 4.0 has drawn considerable attention from industry and academic research communities. The recent advances in Internet of Things (IoT), Big Data analytics, sensor technology, and artificial intelligence have led to the design and implementation of novel approaches to take full advantage of data-driven solutions applicable to Industry 4.0. With the availability of large datasets, it has become crucially important to identify the appropriate amount of relevant information, which would optimize the overall analysis of the corresponding systems. In this article, specific properties of dynamically evolving data systems are introduced and investigated, which provide framework to assess the appropriate amount of representative information.
| Original language | English |
|---|---|
| Article number | 8941297 |
| Pages (from-to) | 6033-6041 |
| Number of pages | 9 |
| Journal | IEEE Transactions on Industrial Informatics |
| Volume | 16 |
| Issue number | 9 |
| Early online date | 24 Dec 2019 |
| DOIs | |
| Publication status | Published - 1 Sept 2020 |
Keywords
- Industry 4.0
- Dynamical Systems
- Network Theory
- Entropy
- entropy
- industry 4.0
- network theory
- Dynamical systems
Research Centres
- Data Science STEM Research Centre
- Data and Complex Systems Research Centre
