Senior Expert Data Scientist at Alstom, France, Andrea Staino joined the company in 2015 to work on development of algorithms for Prognostics and Health Management and in application of data science for innovation for smart mobility systems. He is also Adjunct Professor at Trinity College Dublin, Ireland, from where he received his PhD in 2013. He co-authored more than 30 scientific papers published in different international peer-reviewed scientific journals and conferences.
Sessions
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June 06: Upgrading rail operations and asset management with connectivity and novel technologies
Applying machine learning to mitigate radio disturbances in digital rail systems
Digital transformation plays a key role in enhancing resilience in railway mobility. In particular, reliable train-to-ground radio communication is one of the most important factors in ensuring resilient railway operations. As an open environment, radio can be subject to variations, external interference and degradations which may cause severe disruptions to traffic. The speech discusses how machine learning-based solutions developed in Alstom can improve train operations by improving resilience against radio issues. Thanks to detection, diagnostics and prognostics algorithms, timely alerts are generated and issue resolution is enabled before any service disruption. From design phase to operation and maintenance, the solution increases the efficiency of train-to-ground radio tuning and troubleshooting and transforms the unreliable radio environment into a controlled communication link.
