An Entropy-Based Approach to Real-Time Information Extraction for Industry 4.0

MARCELLO TROVATI, HUAIZHONG ZHANG, JEFFREY RAY, Xiaolong Xu

Research output: Contribution to journalArticle

2 Citations (Scopus)
87 Downloads (Pure)

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 languageEnglish
Article number8941297
Pages (from-to)6033-6041
Number of pages9
JournalIEEE Transactions on Industrial Informatics
Volume16
Issue number9
Early online date24 Dec 2019
DOIs
Publication statusPublished - 1 Sep 2020

Keywords

  • Industry 4.0
  • Dynamical Systems
  • Network Theory
  • Entropy
  • entropy
  • industry 4.0
  • network theory
  • Dynamical systems

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