The increasing demands in mobility bring forth unprecedented challenges in railway infrastructure maintenance and renewals. In taking on this challenge, infrastructure operators need timely information regarding the current (diagnosis) and future (prognosis) condition of their assets. On-Board Monitoring (OBM) techniques attempt to facilitate continuous and data-driven assessment by equipping vehicle with low-cost measuring devices for providing complementary information regarding the state of the railway tracks and rolling stock. This presentation will discuss the use of data-driven and model-assisted methods for derivation of such OBM-based indicators.

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