JITA

JITA Journal of Information Technology and Applications

Vol. 9 No. 2 (2019): JITA - APEIRON

Goran Đukanović, Dragan Popović

MISSION CRITICAL ICT

Original scientific paper

DOI:https://doi.org/ 10.7251/JIT1902060DJ

Abstract

In this paper, three technologies intended to be implemented in Private Mobile Radio systems are analyzed and compared: TETRA (Terrestrial Trunked Radio), LTE (Long Term Evolution) and DMR (Digital Mobile Radio). Characteristics of these networks are collected and compared in one SWOT table. Based on this analysis, appropriate recommendations are made, which should be taken into account when choosing a specific solution for specific uses in Critical Communications systems.

Keywords: DMR, ICT, TETRA.

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.