Multimodal sensing for sustainable structural health monitoring of critical infrastructures and built environment

In the last years, there is an increasing attention to the management and monitoring of critical infrastructure with a particular focus on the transport ones. In fact, several infrastructures have experienced (especially bridges) significant safety criticalities, which in few cases led to collapse with significant social and economic impacts. In this context, Structural Health Monitoring (SHM) is necessary in order to provide information, which can support the strategies for increasing the life-time of the structure, correctly planning maintenance interventions, so to ensure safety conditions of the infrastructure under any environmental condition and hazard occurrence. At the sight of the above considerations, at present, significant research efforts are on-going towards development of SHM systems able to get the opportunity of technological advances in sensing and, at the same time, to be economically sustainable. In particular, there is the necessity to design and implement integration strategies, where the modern sensing technologies, coming from several research fields, are combined with the usual tools and models exploited in civil engineering. Therefore, the present contribution deals with a unified approach to the design and development of systems for early warning, monitoring and quick damage assessment of the built environment and critical infrastructures and networks. In this context, the integration is the key factor for exploiting the synergy among different kind of sensing/diagnostics technologies (including new concept of operation, such as the citizen as a sensor and sensors no sensors) and advanced Spatial Data infrastructure and ICT architectures . It is also important to assimilate monitoring data and indicators coming from the sensing into civil engineering; this is crucial to identify actions and strategies for an effective and economically sustainable management of the infrastructure. In addition, the integrated SHM has to be designed and implemented according to several stages exploiting different sensing technologies, which are organized according to a temporal and logical workflow characterized by different levels of observation and knowledge, where the information gained at a level is used to decide whether to activate the next level. At conference, several examples of the proposed integrated SHM approach will be presented, with a focus on transport infrastructure and built environment.