Developing A Bim-Shm Integrated System For Disaster Risk Management Using Auto-Regressive Model

Nowadays, one of the most prominent and global discussed topics is presenting scientific methods to evaluate potential structural damages to improve infrastructure disaster risk management. the most strategic infrastructure, including buildings, bridges, dams, and oil platforms, typically has high total cost throughout its life-cycle (lynch & loh, 2006).hence, any damage and interruption in its on-going operation will impose prohibitive implications. structural health monitoring (shm) systems have been developed in recent years to aptly determine the damage contingency, level, and location before the structural collapse. these systems can provide decision-makers the required information about the level of structural damage immediately after an earthquake. the current challenge in structural safety management, however, is to find algorithms to process the invaluable data obtained from sensors and to define practical criteria to assess the ongoingstructural health states.