Educational Application of Artificial Intelligence for Diagnosing the State of Railway Tracks

Autor: Dobrivoje Dubljanin, Filip Marković, Gabriela Dimić, Dragan Vučković, Martina Petković, Lazar Mosurović
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: International Journal of Cognitive Research in Science, Engineering and Education, Vol 12, Iss 2 (2024)
Druh dokumentu: article
ISSN: 2334-8496
DOI: 10.23947/2334-8496-2024-12-2-467-476
Popis: The aim of the work is to present an innovative solution based on artificial intelligence for examining the condition of railway tracks in real time. The system, based on fuzzy logic and metaheuristics such as Fuzzy Logic, Neural Networks and Bee Behavior Optimization, combines hardware and software to provide reliable data on the technical characteristics of the railway. Installed in rail vehicles, hardware collects this data, while software uses artificial intelligence to improve operational reliability and safety. The aforementioned technology is not only useful for infrastructure diagnostics, but also for urban railways such as trams and metros, ensuring a high level of passenger safety. The introduction of artificial intelligence in the railway sector is a key step towards modernisation, improving efficiency, resource optimization and safety. Although still in its infancy, artificial intelligence already shows great potential in transforming the railway sector towards a more efficient, reliable and sustainable future.
Databáze: Directory of Open Access Journals