@ARTICLE{Mikołajewski_Dariusz_The_2024,
 author={Mikołajewski, Dariusz and Czerniak, Jacek M. and Piechowiak, Maciej and Węgrzyn-Wolska, Katarzyna and Kacprzyk, Janusz},
 volume={72},
 number={1},
 journal={Bulletin of the Polish Academy of Sciences Technical Sciences},
 pages={e147346},
 howpublished={online},
 year={2024},
 abstract={By reviewing the current state of the art, this paper opens a Special Section titled “The Internet of Things and AI-driven optimization in the Industry 4.0 paradigm”. The topics of this section are part of the broader issues of integration of IoT devices, cloud computing, big data analytics, and artificial intelligence to optimize industrial processes and increase efficiency. It also focuses on how to use modern methods (i.e. computerization, robotization, automation, machine learning, new business models, etc.) to integrate the entire manufacturing industry around current and future economic and social goals. The article presents the state of knowledge on the use of the Internet of Things and optimization based on artificial intelligence within the Industry 4.0 paradigm. The authors review the previous and current state of knowledge in this field and describe known opportunities, limitations, directions for further research, and industrial applications of the most promising ideas and technologies, considering technological, economic, and social opportunities.},
 type={Article},
 title={The Internet of Things and AI-based optimization within the Industry 4.0 paradigm},
 URL={http://www.czasopisma.pan.pl/Content/129260/PDF/BPASTS-03702-EA.pdf},
 doi={10.24425/bpasts.2023.147346},
 keywords={Industry 4.0, Internet of Things, machine learning, cyber-physical system, industrial Internet of Things},
}