Abstract
Intelligent Industrial IoT (IIoT) is a promising tool in the context of the fourth industrial revolution, Industry 4.0. It is reliant on the interaction between computer-integrated manufacturing and Artificial Intelligence (AI) technologies that can lead to the plenty of opportunities for various intelligent industrial services. IIoT is perceived to generate a large volume of industrial data. Thus, it necessitates the emergence of the new data-driven strategies, in which, intelligence is considered to have a fundamental role. In this context, the Machine Learning (ML) techniques are the core branch of AI and capable of extracting valuable information from large quantities of data. As they play an essential role in data mining, knowledge discovering, and building pattern recognition models, they are able to provide a powerful computational paradigm in equipping the embedded intelligence in industrial applications as well. This chapter discusses the opportunities and challenges of realizing the AI, and particularly ML, approaches in IIoT systems that are used in the smart manufacturing environment.
| Original language | English |
|---|---|
| Title of host publication | AI-Enabled Threat Detection and Security Analysis for Industrial IoT |
| Editors | Hadis Karimipour, Farnaz Derakhshan |
| Publisher | Springer, Cham |
| Pages | 7-19 |
| Number of pages | 13 |
| Edition | 1st |
| ISBN (Electronic) | 9783030766139 |
| ISBN (Print) | 9783030766122, 9783030766153 |
| DOIs | |
| Publication status | Published - 5 Aug 2021 |
| Externally published | Yes |