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Smart Structures and Systems
  Volume 31, Number 2, February 2023 , pages 141-154
DOI: https://doi.org/10.12989/sss.2023.31.2.141
 


Feasibility study on using crowdsourced smartphones to estimate buildings' natural frequencies during earthquakes
Ting-Yu Hsu, Yi-Wen Ke, Yo-Ming Hsieh and Chi-Ting Weng

 
Abstract
    After an earthquake, information regarding potential damage to buildings close to the epicenter is very important during the initial emergency response. This study proposes the use of crowdsourced measured acceleration response data collected from smartphones located within buildings to perform system identification of building structures during earthquake excitations, and the feasibility of the proposed approach is studied. The principal advantage of using crowdsourced smartphone data is the potential to determine the condition of millions of buildings without incurring hardware, installation, and long-term maintenance costs. This study's goal is to assess the feasibility of identifying the lowest fundamental natural frequencies of buildings without knowing the orientations and precise locations of the crowds' smartphones in advance. Both input-output and output-only identification methods are used to identify the lowest fundamental natural frequencies of numerical finite element models of a real building structure. The effects of time synchronization and the orientation alignment between nearby smartphones on the identification results are discussed, and the proposed approach's performance is verified using large-scale shake table tests of a scaled steel building. The presented results illustrate the potential of using crowdsourced smartphone data with the proposed approach to identify the lowest fundamental natural frequencies of building structures, information that should be valuable in making emergency response decisions.
 
Key Words
    crowdsourcing; fundamental natural frequency; orientation alignment; post-earthquake building safety; smartphones
 
Address
Department of Civil and Construction Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan.
 

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