ISSN: 2490-3477

E-ISSN: 2490-3485

TTTP

Traffic and Transport Theory and Practice

Journal for Traffic and Transport Research and Application

Vol. 1 No. 1 (2016): TTTP - APEIRON

Mladen Dobrić, Milica Miličić, Pavle Gladović, Filip Dobrić

Application of Modern Information Systems for More Efficient Removal of Parking Violators

Original scientific paper

DOI: 10.7251/JTTTP1601061D

Abstract

PUC „Parking servis“ Novi Sad, which has parking spaces organization and exploitation as its narrower activity, in its structure has the Transportation Office whose main task is the removal of parking violators by the order of a competent authority. In this paper Transportation Service’s work or- ganization, transport organization and potential upgrades in business conduct via modern information technologies, will, above all, be considered, as well as the roll of the Transportation Service inside the system of PUC „Parking servis“, and it’s contribution to the Company, from a financial aspect. Described income and cost data are based on the company’s data of business conduct in 2013. Three main mea- sure suggestions will be considered, all based on advanced use of information technologies, implemen- tation of a dispatching unit, and suitable patrol unit- Vehicle of Observatory Purpose (VOP)- maximum, minimum, and real, type of advanced business management.

Keywords : GPS, Modern information technologies, Organization of transport, removal of parking viola- tors.

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.