Real-time diagnostics of the technical condition of moving railway rolling stock and an artificial intelligence–based system for enhancing safety

Abstract

Ensuring safety in railway transport has always been a priority. This article explores the technological
capabilities of real-time diagnostics of the technical condition of moving railway rolling stock through
IoT sensors, GPS, 5G, LoRaWAN, and artificial intelligence algorithms. It discusses the principle of
operation of modern monitoring systems, the detection of technical failures, and the role of intelligent
anomaly detection in enhancing railway safety. The analysis shows that real-time diagnostics
significantly improve the early detection of technical issues, increase the safety of wagon movement, and
reduce the risk of accidents.