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New trends for structural health monitoring of bridges

Structural health monitoring ( has been a promising tool in management activities of bridges.
To deal with large amounts of data, SHM has been cast in the context of a statistical pattern recognition (SPR) paradigm.

Meanwhile, recent technologies have unveiled alternative sensing opportunities and new perspectives to manage and observe the response of bridges, but it is widely recognized that bridge SHM is not yet fully capable of producing reliable global information on the presence of damage.

Therefore, the main goal of this presentation is to point out key developments in research and applications of the SPR paradigm observed in bridges in the last three decades, including developments in sensing and in machine learning for data analysis, and to identify current trends to promote more coordinated and interdisciplinary research in the SHM of bridges.