For the application of structural health monitoring (SHM) system to the post-earthquake damage screening of building structures, an immediate evaluation of the degree of damage in primary structural components is a challenging task. To increase the resolution in damage detection above a certain level to detect damage in individual components, a SHM requires the use of a dense array of sensors deployed to building structures. In order to deal with a large amount of data acquired by the sensing network and to distribute quick safety alerts on the condition of earthquake-affected buildings, a SHM system that is connected with a cyberinfrastructure specifically designed for the autonomous structural integrity assessment of buildings is developed. In the system, big data transferred from a dense sensing network is automatically stored and processed to extract damage features using a PostgresSQL relational database and embedded local damage detection algorithms. In a benchmark study, the schema of the SHM system is specifically designed to function with a built-in local damage detection algorithm that needs a comparative study of current dataset with past reference dataset. To visualize the results of the damage detection analysis, a PHP-based web-viewer is also designed for the SHM system. Finally, the performance of the developed cyber-based SHM system is evaluated through a series of the damage detection tests on a 5-story steel testbed frame that can replicate damage in beams and columns.
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