Structural health monitoring is effective if it allows us to identify the condition state of a structure with an appropriate level of confidence. The estimation of the uncertainty of the condition state is relatively straightforward a posteriori, i.e., when monitoring data are available. However, monitoring observations are not available when designing a monitoring system; therefore, the expected uncertainty must be estimated beforehand. This paper proposes a framework to evaluate the effectiveness of a monitoring system accounting for temperature compensation. This method is applied to the design process of a structural health monitoring system for civil infrastructure. In particular, the focus is on the condition-state parameters representing the structural long-term response trend, e.g., due to creep and shrinkage effects, and the tension losses in prestressed concrete bridges. The result is a simple-to-use equation that estimates the expected uncertainty of a long-term response trend of temperature-compensated response measurements in the design phase. The equation shows that the condition-state uncertainty is affected by the measurement and model uncertainties, the start date and duration of the monitoring activity, and the sampling frequency. We validated our approach on a real-life case study: the Colle Isarco viaduct. We verified whether the pre-posterior estimation of expected uncertainty, performed with the experimented approach, is consistent with the real uncertainty estimated a posteriori based on the monitoring data.

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This paper explores the potential of satellite Interferometric Synthetic Aperture Radar (InSAR) technology for Structural Health Monitoring (SHM) of road bridges. While many road bridges worldwide are over half a century old and exhibit widespread deterioration, traditional contact-type sensors for SHM are installed only on a few structures, mainly due to their high cost. In recent years, remote sensing techniques, such as satellite InSAR technology, have been explored to overcome these limitations. This paper focuses on the displacements of the Po River Bridge, which is part of the Italian A22 Highway. We extract the bridge's displacement with Multi-Temporal InSAR data processing using SAR images acquired by the Italian Cosmo-SkyMed mission. We study 8 years of displacement time series of reflective targets, Persistent Scatterers, naturally visible on the bridge without installing any instrumentation on site. We perform an exploratory analysis of the displacements of the entire area through the K-means clustering algorithms and investigate the correlation between the bridge displacements and environmental phenomena (variation of air temperature and river water flow). The results confirm the potential of satellite InSAR technology for the remote monitoring of road bridges and their surrounding area. However, they also highlight the need for a metrological validation of such technology through a direct comparison with measurements from traditional and already validated SHM systems.

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