Industrial Internet of Things: A Review of Improvements Over Traditional SCADA Systems for Industrial Automation

field_of_study

Blank

university

Palestine Technical College

authors

Babayigit B.; Abubaker M.

authors_full_names

Babayigit, Bilal (14010616400); Abubaker, Mohammed (58170618100)

authors_id

14010616400; 58170618100

year

2024

source_title

IEEE Systems Journal

article_title

Industrial Internet of Things: A Review of Improvements Over Traditional SCADA Systems for Industrial Automation

volume

18

issue

1

page_start

120

page_end

133

publisher

Institute of Electrical and Electronics Engineers Inc.

affiliations

Erciyes University, Department of Computer Engineering, Melikgazi, 38039, Turkey; Palestine Technical College, Gaza, P920, Palestine

authors_with_affiliations

Babayigit B., Erciyes University, Department of Computer Engineering, Melikgazi, 38039, Turkey; Abubaker M., Erciyes University, Department of Computer Engineering, Melikgazi, 38039, Turkey, Palestine Technical College, Gaza, P920, Palestine

corresponding_author

M. Abubaker; Erciyes University, Department of Computer Engineering, Melikgazi, 38039, Turkey; email: mabubaker@ptcdb.edu.ps

cited_by

95

doi

10.1109/JSYST.2023.3270620

author_keywords

Deep learning (DL); digital twin (DT); IIoT protocols; industrial Internet of Things (IIoT); Internet of Things (IoT); machine learning (ML); security; supervisory control and data acquisition (SCADA)

index_keywords

Automation; Deep learning; E-learning; Internet protocols; Network architecture; Real time systems; SCADA systems; Deep learning; Digital twin; Industrial internet of thing; Industrial internet of thing protocol; Internet of thing; Machine learning; Machine-learning; Security; Supervisory control and data acquisition; Internet of things