A structural health monitoring (SHM) system monitors the condition of structures such as tall buildings and promptly and quantitatively evaluates their deterioration and damage due to natural hazards and aging. The system is under keen attention for prolonging the structures' lives and increasing their durability while keeping them in healthy condition. Several SHM systems have been proposed and tested for experiments or for real structures. However, most of these systems are customized to particular structures, so that they are not sufficiently scalable. Moreover, there is no standard data format for the data they gather. Thus, it is difficult to treat the data stochastically. We have been developing smart sensor units with data acquisition and data management capability. Many data analysis tools utilizing system identification and an easy-to-use user interface for SHM have been also studied. The SHM platform consists of these tools to evaluate the soundness of building structures, the server system to publish the diagnosis results to the users, and the smart sensor units for automatic data management. Moreover, as it has a flexible data model and an automatic data entry system for acquired data, the system can be applied to any building structures for treating them from a stochastic viewpoint. In addition, the smart sensor unit we developed shortens the configuration process and enables us to control the measurement configuration through a web interface. This study presents the key features of the SHM platform.
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