Häftad, Engelska, 2026
Artificial Intelligence Methods in Railway Infrastructure Systems
Application of Data-Centric Engineering
Av Diogo Ribeiro, Araliya Mosleh, Andreia Meixedo, Abdollah Malekjafarian, Ramin Ghiasi, Meisam Gordan
4579 kr
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Beskrivning
This book acts as a vital reference for those seeking to understand and implement AI-driven solutions in railway systems, encouraging the adoption of anticipatory strategies to shape future trends. Readers will discover how AI innovations can streamline operations, optimize resource allocation, and significantly improve network safety, making it an essential guide for professionals looking to stay ahead in the evolving field of railway infrastructure management.
- Covers the diverse array of Artificial Intelligence (AI) tools that can address the complex challenges associated with railway infrastructure management
- Explores AI capabilities in the continuous monitoring of railway infrastructure, providing real-time insights into the condition of tracks, bridges, tunnels, and other critical assets
- Leverages the potential of AI in the automatization of inspection processes, reducing the need for manual intervention and improving the efficiency and accuracy of assessments
- Presents AI algorithms for early anomaly detection or deviations from normal operating conditions, alerting infrastructure managers to potential issues before they escalate
Produktinformation
- Utgivningsdatum: 2026-11-16
- Mått: 152 x 229 x undefined mm
- Format: Häftad
- Språk: Engelska
- Antal sidor: 500
- Förlag: Elsevier Science
- ISBN: 9780443337796
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Mer information
Dr Ribeiro is Professor at Instituto Superior de Engenharia do Porto in Portugal. He is a Member of the Institute of R&D in Structures and Construction (CONSTRUCT), coordinator or researcher on more than 20 R&D projects funded by industry, FCT and EU programs in the field of railway infrastructures and digital construction Araliya Mosleh is a senior researcher at the Faculty of Civil Engineering, University of Porto. She obtained her PhD degree in 2016 from the University of Aveiro, Portugal. Since then she has actively engaged in 9 national and international projects in the field of railway infrastructure. She was a visiting researcher at Bundeswehr University (2015), Wollongong University (2017), and Evoleo Company (2019) Andreia Meixedo holds a Master in Structural Engineering (2012) and a PhD in Civil Engineering (2021), all from the University of Porto. Her main research experience is related to damage identification, structural health monitoring, machine learning, railway infrastructures, wayside and onboard condition monitoring; weigh-in-motion; advanced models for analysis of the bridge-track-train dynamic interaction, structural testing and experimentation, model calibration and validation Dr. Abdollah Malekjafarian is currently an Assistant Professor and leader of the “Structural Dynamics and Assessment Laboratory (SDA-Lab), in the School of Civil Engineering at University College Dublin (UCD), in Ireland. He received his PhD in Civil Engineering from UCD in 2016. His main areas of research interest are structural dynamics and random vibrations for civil infrastructure including wind turbines and transport Infrastructure. Dr. Malekjafarian is also the Coordinator of the WindLEDeRR project (Lifetime Extension Decommissioning Repowering Repurposing), a comprehensive decision support tool for end-of-life wind turbines in Ireland.Dr Ramin Ghiasi is a Postdoctoral Research Fellow at the School of Civil Engineering, University College Dublin, Ireland. His research interests encompass civil structure and infrastructure health monitoring (including transport infrastructure, offshore wind turbines, and tall buildings), the application of AI and optimization methods in civil engineering, and the creation of IoT-based monitoring systemsDr Meisam Gordan is currently a Postdoctoral Research Fellow at University College Dublin, working on the Di-Rail project, which focuses on automated and rapid fault diagnosis of railway tracks using in-service train measurements. His research interests include: structural health monitoring, data mining, critical infrastructure resilience, Industry 4.0, big data and smart cities
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