Skip to content
akaturk Academic measurement

Article detail · 2021 · article

Smart Diagnosis And Maintenance Systems For Railway Tracks

Journal Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi
ISSN2636-820X
YÖKSİS OpenAlex Open access · bronze TR Index
Year2021
Citations2OpenAlex
Percentile%36.5
FWCI0.11.00 = world average

Data source split

  • YÖKSİSYÖKSİS article record
  • YÖKSİS venueAkıllı Ulaşım Sistemleri ve Uygulamaları Dergisi
  • OpenAlexOpenAlex enrichment (abstract, citations, topics)
  • Semantic Scholarcitation count (not merged with OpenAlex)

Abstract

OpenAlex English

In recent years, advanced technologies such as artificial intelligence (AI), the internet of things (IoT), and big data came into prominence. These technologies found an extensive area of utilization in various sectors. Railway systems as an important part of the transportation of people and goods should be improved by the integration of novel technologies. Successful detection of track faults and operating maintenance tasks accordingly are essential for the safety of railway operations. Currently, image processing and pattern recognition via machine learning applications are in common use for automated track inspections. However, it is not possible to claim that railway tracks are integrated with current technology perfectly. In this work, differences between the traditional way and the smart way of track inspection and maintenance are presented. Shortcomings of the application of advanced technologies into railway tracks are detected and required actions for further improvements are discussed. Lastly, the effects of the use of smart systems on the life cycle of the structures are evaluated.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

2citationsOpenAlex · cited_by_count (cache / database)

Authors

4
  1. ERDEM BALCI ZONGULDAK BÜLENT ECEVİT ÜNİVERSİTESİ 1
  2. Tunay Uzbay Yelce 2
  3. ERTAN YALÇIN 3
  4. NİYAZİ ÖZGÜR BEZGİN 4