Guest Editorial: Data Science Challenges in Industry 4.0

Francesco Piccialli, Nik Bessis, Jason J. Jung

Research output: Contribution to journalArticle (journal)peer-review

4 Citations (Scopus)

Abstract

Everyone, knowingly or not, is in a position to generate data at all times in our lives. Mainly in the professional life, where the production of data is addressed and aimed at achieving a series of objectives, and in social and personal life where the production of data, direct and indirect, is equally important although not always clearly identifiable. Always and in any case, the representation of our actions in digital contents or the analysis of our behaviour as consumers, just to give two examples, are a common denominator of our relationship with the digital framework which has a direct impact at the level of relationship with companies or with public administrations. In the business, the most appropriate example today is that of Industry 4.0 which with the virtualization of the processes and products themselves is allowing companies to explore novel paradigms of innovation that were once unthinkable.
Original languageUndefined/Unknown
Pages (from-to)5924-28
JournalIEEE Transactions on Industrial Informatics
Volume16
Issue number19
Early online date2 Apr 2020
DOIs
Publication statusPublished - 1 Sep 2020

Keywords

  • data science
  • industry 4.0
  • machine learning
  • Internet of things
  • deep learning
  • industrial revolution

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