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Vol. 6 No. 2 (2018): JITA - APEIRON

Sanja Bauk, Diego Garcia Gonzalez, Anke Schmeink, Zoran Ž Avramović

MANET vs. ZigBee: Some simulation experiments at the seaport environment

Original scientific paper

DOI: https://doi.org/10.7251/JIT1602063B

Abstract

The paper presents the results of some OPNET simulation experiments realized with an aim to benchmark MANET and ZigBee networks’ performances at the seaport environment. The MANET is formed among workers’ and supervisors’ personal digital assistants (PDAs). On the other side, the ZigBee is established between end-nodes or employees’ body central units (BCUs), which collect signals from several active and passive devices embedded into ID badges and personal protective equipment (PPE) pieces; several moving and fixed routers; and the coordinator mounted at the appropriate seaport location. The simulation experiments are realized over the layout of the Port of Bar (Montenegro) container and general cargo terminal by taking into account the real number of workers and supervisors engaged at the terminal per each shift. This research work should give an insight to the seaport’s managers and stakeholders into some advantages and disadvantages of these two considered wireless networks’ schemes, and to motivate them to provide conditions for implementing these or similar on seaport and backend info-communication solutions for uprising the level of occupational safety and overall seaport’s environmental management system.

Keywords: MANET, ZigBee, seaport, occupational safety.

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.