Applications of Artificial Intelligence (AI) has revolutionized the railway sector in recent years and are increasingly essential to the modernization of the railway industry. By making significant improvements in operational efficiency, safety, digital infrastructure, security, and passenger satisfaction, AI and its sub domains such as Machine Learning (ML), Deep Learning (DL) etc. have become integral to railway systems worldwide. This paper presents an in-depth analysis and review of AI applications across multiple domains of railways, including monitoring, predictive maintenance, traffic management, and passenger services etc. The role of AI extends beyond data prediction, maintenance, and management to the design and deployment of advanced controllers now used in rail vehicles. Furthermore, this paper highlights the contribution of AI algorithms to cybersecurity, particularly in preventing cyber-attacks on railway infrastructure. Several case studies are discussed to provide deeper insights into how AI algorithms are transforming modern railways into efficient, resilient, and passenger-centric systems. This paper provides a comprehensive review of AI applications with bibliometric analysis in almost all the domains of railway system with 360-degree coverage. It also discusses the strengths and limitations of present AI applications and highlights the gap analysis with expected future trends.
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