Project detail


Type of structure




Why monitoring

  • Assess the structural behaviour of the bridge under traffic loads
  • Notify any anomalous structural modification that may occur during the service life
  • Set thresholds values to the expected traffic load to preserve the safety design level
  • Reduce the collapse risk by enhancing the knowledge on existing infrastructure
  • Plan efficient maintenance interventions

Interventions in synthesis

  • Type of devices : Clinometers
  • Number of sensors : 80
  • Installation time : February 2016
  • Analyzed data : Bridge deck rotation


The main goal was to provide infrastructure owners with useful information regarding the bridge structural behaviour, in order to predict possible failures and damage/deterioration processes as well as show bridge responses under different load conditions.

The monitoring need was originated by the brittle failure of one span belonging to one carriage way during its demolition. The failure was generated due to a discrepancy between as built drawings and actual structure, in particular with reference to pre-stressed tendons layout.

In order to capture the bridge deformation under traffic excitations, a total number of 80 integrated MEMS sensors have been instrumented on the bridge, 35 in the North and 40 in the South spans respectively. Sensors have been instrumented at the bottom of every girder and connected to a control unit which sends data directly to the cloud in real-time.

The collected data have been post-processed via specific algorithms performing a structural interpretation of the measurements, aimed to investigate the safety threshold levels reached by the viaduct. The bridge deformations were compared in real time with a set of alerts limits representing increasing danger levels. A first alert threshold was set to represent the maximum deformation expected under the design traffic loads. A second more onerous alert level was set to be triggered by a monitored deformation corresponding to permanent structural damages. The collected measurements were compared with the threshold values in streaming.

The analysis of the data evolution in time allowed the client to evaluate the safety of the monitored structure, to identify timeframes in which the vehicular traffic has been interrupted and to control the transition of exceptional lorries.