Machine Learning for Industrial Internet of Things (IIoT)

Submission Deadline: 31 January 2023 (closed) Submit to Special Issue

Guest Editors

Dr. Jawad Ahmad, Edinburgh Napier University, UK.
Dr. Arshad Arshad, University of Strathclyde, UK.
Dr. Syed Aziz Shah, Coventry University, UK.
Dr. Nick Pitropakis, Edinburgh Napier University, UK.


The Internet of Things (IoT) is a term that refers to widespread connectivity between everyday devices and the Internet. IoT works by deploying thousands of smart devices in residential and industrial settings. These devices gather data from their surroundings, conduct desired processing operations on the data, and send the processed data via secure, dependable communication channels. In terms of time, energy, and cost savings, recent developments in software, hardware, and communication technologies have considerably enhanced human lifestyles. The phrase "Industrial Internet of Things" (IIoT) refers to the implementation of traditional Internet of Things concepts in industrial settings. In an industrial setting, the IIoT optimises manufacturing methods by enabling sustainable and efficient solutions. The IIoT market is currently experiencing tremendous expansion, as well as increased adaptability in many sectors' digital transitions. Strong partnerships and common interests among IIoT stakeholders and developing applications have enticed large corporations from around the world to engage in this growing market. In this regard, we encourage academics to submit original research articles as well as review articles that will aim to explore novel machine learning-based techniques in the area of Industrial IoT.


Machine Learning, IoT, Cybersecurity, Multimedia Encryption, Classification, Smart Systems, Cybersecurity

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