Community-Based Multi-Sensory Structural Health Monitoring

Assessing the structural integrity of buildings after an earthquake is necessary for citizens to be able to use these facilities safely after the event. The currently available structural health monitoring (SHM) systems use a dense network of sensors installed in buildings to monitor their behavior during earthquakes. Such a network is impractical with respect to cost and deployment time for the vast majority of buildings; therefore, most structures remain uninstrumented. However, a massive network of citizen-owned smart devices, such as tablets and smartphones that contain cameras and vibration sensors, has already been deployed. This paper develops a framework that can crowdsource readings from distributed citizen-owned smart devices and convert these readings into actionable information. Although prior community-based seismic research focused on using smartphones to provide early disaster warnings, the proposed system focuses specifically on using video captured on a smartphone to directly assess the structural health of buildings post-earthquake, thus providing citizens and emergency personnel with immediate relevant information regarding the health state of buildings. This paper presents a novel self-calibration technique for a smartphone camera using its internal accelerometer readings. Shake table experiments show that the proposed technique can achieve sub-millimeter accuracy, demonstrating its suitability for SHM applications