IIoT/IoT and Artificial Intelligence/Machine Learning as a Process Optimization driver under industry 4.0 model


  • Federico Walas Universidad Nacional de La Plata, Argentina
  • Andrés Redchuk Universidad Nacional de Lomas de Zamora. Facultad de Ingeniería. Buenos Aires, Argentina.




Artificial Intelligence, IIoT, IoT, machine learning, Industry 4.0


The advance of digitalization in industry is making possible that connected products and processes help people, industrial plants and equipment to be more productive and efficient, and the results for operative processes should impact throughout the economy and the environment.
Connected products and processes generate data that is being seen as a key source of competitive advantage, and the management and processing of that data is generating new challenges in the industrial environment.
The article to be presented looks into the framework of the adoption of Artificial Intelligence and Machine Learning and its integration with IIoT or IoT under industry 4.0, or smart manufacturing framework. This work is focused on the discussion around Artificial Intelligence/Machine Learning and IIoT/IoT as driver for Industrial Process optimization.
The paper explore some related articles that were find relevant to start the discussion, and includes a bibliometric analysis of the key topics around Artificial Intelligence/Machine Learning as a value added solution for process optimization under Industry 4.0 or Smart Manufacturing paradigm.
The main findings are related to the importance that the subject has acquired since 2013 in terms of published articles, and the complexity of the approach of the issue proposed by this work in the industrial environment.


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How to Cite

Walas, F., & Redchuk, A. . (2021). IIoT/IoT and Artificial Intelligence/Machine Learning as a Process Optimization driver under industry 4.0 model. Journal of Computer Science and Technology, 21(2), e15. https://doi.org/10.24215/16666038.21.e15



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