{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T00:42:19Z","timestamp":1760488939987,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2020,6,15]],"date-time":"2020-06-15T00:00:00Z","timestamp":1592179200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Science and Technology","award":["108-2622-M-011-001-C22"],"award-info":[{"award-number":["108-2622-M-011-001-C22"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Computer vision-based approaches are very useful for dynamic displacement measurement, damage detection, and structural health monitoring. However, for the application using a large number of existing cameras in buildings, the computational cost of videos from dozens of cameras using a centralized computer becomes a huge burden. Moreover, when a manual process is required for processing the videos, prompt safety assessment of tens of thousands of buildings after a catastrophic earthquake striking a megacity becomes very challenging. Therefore, a decentralized and fully automatic computer vision-based approach for prompt building safety assessment and decision-making is desired for practical applications. In this study, a prototype of a novel stand-alone smart camera system for measuring interstory drifts was developed. The proposed system is composed of a single camera, a single-board computer, and two accelerometers with a microcontroller unit. The system is capable of compensating for rotational effects of the camera during earthquake excitations. Furthermore, by fusing the camera-based interstory drifts with the accelerometer-based ones, the interstory drifts can be measured accurately even when residual interstory drifts exist. Algorithms used to compensate for the camera\u2019s rotational effects, algorithms used to track the movement of three targets within three regions of interest, artificial neural networks used to convert the interstory drifts to engineering units, and some necessary signal processing algorithms, including interpolation, cross-correlation, and filtering algorithms, were embedded in the smart camera system. As a result, online processing of the video data and acceleration data using decentralized computational resources is achieved in each individual smart camera system to obtain interstory drifts. Using the maximum interstory drifts measured during an earthquake, the safety of a building can be assessed right after the earthquake excitation. We validated the feasibility of the prototype of the proposed smart camera system through the use of large-scale shaking table tests of a steel building. The results show that the proposed smart camera system had very promising results in terms of assessing the safety of steel building specimens after earthquake excitations.<\/jats:p>","DOI":"10.3390\/s20123374","type":"journal-article","created":{"date-parts":[[2020,6,15]],"date-time":"2020-06-15T12:16:57Z","timestamp":1592223417000},"page":"3374","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A Stand-Alone Smart Camera System for Online Post-Earthquake Building Safety Assessment"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3279-8996","authenticated-orcid":false,"given":"Ting-Yu","family":"Hsu","sequence":"first","affiliation":[{"name":"Department of Civil and Construction Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan"}]},{"given":"Xiang-Ju","family":"Kuo","sequence":"additional","affiliation":[{"name":"Department of Civil and Construction Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Naeim, F., Hagie, S., Alimoradi, A., and Miranda, E. (2006). Automated post-earthquake damage assessment of instrumented buildings. Advances in Earthquake Engineering for Urban Risk Reduction, Springer.","DOI":"10.1007\/1-4020-4571-9_8"},{"key":"ref_2","unstructured":"Federal Emergency Management Agency (2013). HAZUS-MH2.1 Technical Manual, Federal Emergency Management Agency."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1675","DOI":"10.1109\/TMECH.2013.2275187","article-title":"Displacement estimation using multimetric data fusion","volume":"18","author":"Park","year":"2013","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"e2122","DOI":"10.1002\/stc.2122","article-title":"Visual\u2013inertial displacement sensing using data fusion of vision-based displacement with acceleration","volume":"25","author":"Park","year":"2018","journal-title":"Struct. Control Health Monit"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Trapani, D., Maroni, A., Debiasi, E., and Zonta, D. (2015, January 9\u201310). Uncertainty evaluation of after-earthquake damage detection strategy. Proceedings of the IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS), Trento, Italy.","DOI":"10.1109\/EESMS.2015.7175864"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.ndteint.2015.12.006","article-title":"Real-time, non-contact and targetless measurement of vertical deflection of bridges using off-axis digital image correlation","volume":"79","author":"Pan","year":"2016","journal-title":"NDT E Int."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"e2155","DOI":"10.1002\/stc.2155","article-title":"A non-contact vision-based system for multipoint displacement monitoring in a cable-stayed footbridge","volume":"25","author":"Xu","year":"2018","journal-title":"Struct. Control Health Monit."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.ndteint.2013.05.002","article-title":"Dynamic characteristics of suspension bridge hanger cables using digital image processing","volume":"59","author":"Kim","year":"2013","journal-title":"NDT E Int."},{"key":"ref_9","unstructured":"Yoon, H. (2016). Enabling Smart City Resilience: Post-Disaster Response and Structural Health Monitoring. [Ph.D. Thesis, University of Illinois at Urbana-Champaign]."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1405","DOI":"10.1002\/stc.1850","article-title":"Target-free approach for vision-based structural system identification using consumergrade cameras","volume":"23","author":"Yoon","year":"2016","journal-title":"Struct. Control Health Monit."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"876","DOI":"10.1002\/stc.1819","article-title":"Vision-based multipoint displacement measurement for structural health monitoring","volume":"23","author":"Feng","year":"2016","journal-title":"Struct. Control Health Monit."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.jsv.2015.01.024","article-title":"Modal identification of simple structures with high-speed video using motion magnification","volume":"345","author":"Chen","year":"2015","journal-title":"J. Sound Vib."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Wadhwa, N., Rubinstein, M., Durand, F., and Freeman, W.T. (2013). Phase-based video motion processing. ACM Trans. Graph., 32.","DOI":"10.1145\/2461912.2461966"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"106911","DOI":"10.1016\/j.measurement.2019.106911","article-title":"Pixel-based operating modes from surveillance videos for structural vibration monitoring: A preliminary experimental study","volume":"148","author":"Hosseinzadeh","year":"2019","journal-title":"Measurement"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.measurement.2014.10.039","article-title":"A preliminary study on the response of steel structures using surveillance camera image with vision-based method during the Great East Japan Earthquake","volume":"62","author":"Cheng","year":"2015","journal-title":"Measurement"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"7103039","DOI":"10.1155\/2016\/7103039","article-title":"A review of machine vision-based structural health monitoring: Methodologies and applications","volume":"2016","author":"Ye","year":"2016","journal-title":"J. Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1007\/s13349-017-0261-4","article-title":"Review of machine-vision based methodologies for displacement measurement in civil structures","volume":"8","author":"Xu","year":"2018","journal-title":"J. Civ. Struct. Health Monit."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.engstruct.2017.11.018","article-title":"Computer vision for SHM of civil infrastructure: From dynamic response measurement to damage detection\u2014A review","volume":"156","author":"Feng","year":"2018","journal-title":"Eng. Struct."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"e2321","DOI":"10.1002\/stc.2321","article-title":"A literature review of next-generation smart sensing technology in structural health monitoring","volume":"26","author":"Sony","year":"2019","journal-title":"Struct. Control Health Monit."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.eng.2018.11.030","article-title":"Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring","volume":"5","author":"Spencer","year":"2019","journal-title":"Engineering"},{"key":"ref_21","first-page":"531","article-title":"Post-earthquake Building Safety Evaluation Using Consumer-grade Surveillance Cameras","volume":"25","author":"Hsu","year":"2020","journal-title":"Smart Struct. Syst."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.engstruct.2018.08.087","article-title":"Direct measurement of building transient and residual drift using an optical sensor system","volume":"176","author":"Petrone","year":"2018","journal-title":"Eng. Struct."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"e2235","DOI":"10.1002\/stc.2235","article-title":"Vision-based vibration monitoring using existing cameras installed within a building","volume":"25","author":"Harvey","year":"2018","journal-title":"Struct. Control Health Monit."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Hsu, T.Y., and Kuo, X.J. (2020). PDP method to compensate for rotational effect when using a single surveillance camera for interstory drift measurement. Meas. Sci. Technol.","DOI":"10.1088\/1361-6501\/ab833d"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"125019","DOI":"10.1088\/0964-1726\/21\/12\/125019","article-title":"An advanced vision-based system for real-time displacement measurement of high-rise buildings","volume":"21","author":"Lee","year":"2012","journal-title":"Smart Mater. Struct."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","article-title":"A threshold selection method from gray-level histograms","volume":"9","author":"Otsu","year":"1979","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Koo, G., Kim, K., Chung, J.Y., Choi, J., Kwon, N.Y., Kang, D.Y., and Sohn, H. (2017). Development of a High Precision Displacement Measurement System by Fusing a Low Cost RTK-GPS Sensor and a Force Feedback Accelerometer for Infrastructure Monitoring. 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