TY - JOUR
T1 - Community-Based Multi-Sensory Structural Health Monitoring System: A Smartphone Accelerometer and Camera Fusion Approach
AU - Alzughaibi, Ahmed A.
AU - Ibrahim, Ahmed M.
AU - Na, Yunsu
AU - El-Tawil, Sherif
AU - Eltawil, Ahmed
N1 - KAUST Repository Item: Exported on 2021-08-10
Acknowledgements: This work was supported by the National Science Foundation under Award Numbers CMMI:1362547, CMMI:1362458, and OAC:1638186.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/670499
UR - https://ieeexplore.ieee.org/document/9489281/
UR - http://www.scopus.com/inward/record.url?scp=85110911353&partnerID=8YFLogxK
U2 - 10.1109/JSEN.2021.3097696
DO - 10.1109/JSEN.2021.3097696
M3 - Article
SN - 2379-9153
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
ER -