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Vol. 12 No. 1 (2022): JITA - APEIRON

Dražen Marinković, Zoran Ž. Avramović

IoT – Company Approach to IoT Modeling and Applications

Original scientific paper

DOI:https://doi.org/10.7251/JIT2201048M

Abstract

Using the available literature, this paper attempts to present the company ‘s approach to IoT modeling and the incorporation of IoT technologies into business processes. Furthermore, a comprehensive overview of IoT technologies and systems of large corporations (Yokogawa, Intel) and commercial access to IoT technologies is provided. In conclusion, based on previous knowledge and scientifically based arguments, the advantages and disadvantages of IoT technologies are presented.

Keywords: IoT, IioT, Digital Intelligence, Total Cost of Ownership, Operations Excellence, Cloud, CloudIoT.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.