JITA

JITA Journal of Information Technology and Applications

Vol. 6 No. 1 (2018): JITA - APEIRON

Milenko Čabarkapa, Zoran Ž Avramović

Road Safety Management in Local Communities

Original scientific paper

DOI: https://doi.org/10.7251/JIT16027C

Abstract

The research of coordination of activities and responsibility-sharing at the appropriate level of road safety management, conducted by analyzing responses from the prepared Questionnaire, in the period before and after the adoption of the Global Plan for the Decade of action for road safety 2011-2020, showed that the improvement or deterioration of the state of road safety at all levels of management, particularly at the local level within Montenegro, can be directly associated with the achievement of coordination of activities and responsibility sharing for the state of road safety. The aim of the paper is to encourage the development of the road safety system in local communities, basing on a vertical coordination in national and local activities and horizontal coordination in activities at the local level, with the establishment of a responsibility sharing system for the state of road safety in local communities.

Keywords: activity, coordination, responsibility, road safety, level of territorial organisation, local community.

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.