The University of Delaware, one of the nine university partners in the National University Rail Center of Excellence (NURail CoE), a federally funded consortium led by the University of Illinois at Urbana-Champaign, hosted the Big Data Conference on December 11-12, in Newark, Delaware.
Approximately 160 guests — which included representatives from the Federal Railroad Administration, US Department of Transportation, most Class I railroads, suppliers and academics — attended this year’s conference which introduced new and emerging analysis techniques and how those methods can be applied to the large volume of inspection and operational data collected by railways to improve maintenance programs.
Three NURail CoE partners presented research during the conference, including the University of Delaware, Rutgers University, and the University of Illinois at Urbana-Champaign.
Piero Caputo, Jeremiah Dzeble, and Monique Head, all of the University of Delaware, presented their research on “Multipoint Vision-based Wayside Monitoring to Estimate Track Moduli.” Joseph Palese, a research assistant professor at the University of Delaware, joined Abel Ayele of Amtrak to present research on “Assessment of Railway Track Geometry Condition Using Advanced Machine Learning Techniques.”
Asim Zaman, a project engineer at Rutgers University, presented his research on “Artificial Intelligence Aided Stopped on Tracks Analysis: A Case Study on the Effects of Dynamic Envelope Pavement Markings.”
Arthur Lima, a UIUC senior research engineer, presented his research on “Cross-Correlation-Based Railway Change Detection: A Novel Approach for Maintenance Detection.” UIUC Graduate Research Assistants Augusto Ramos, Gustavo Ramos, Panshul Jindal, and Yash Kakde assisted with the research. J. Riley Edwards, senior associate director of NURail CoE, also was in attendance at the conference which focuses on the specific needs of railways and the practical application of data analytics to both infrastructure and rolling stock maintenance planning.
