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• W3113221390 abstract "Using low-cost piezoelectric sensors to sense structural vibration exhibits great potential in augmenting structural engineering, which is yet to be explored in the literature to the best of our knowledge. Examples of such unexplored augmentation include classifying diverse structures (such as building, flyover, foot over-bridge, etc.), and relating the extent of vibration generated at different height of a structure and the associated height. Accordingly, to explore these cases, we develop a low-cost piezoelectric sensor-based vibration sensing system aiming to remotely collect real vibration data from diversified civil structures. We dig into our collected sensed data to classify five different types of structures through rigorous statistical and machine-learning-based analyses. Our analyses achieve a classification accuracy of up to 97% with an F1 score of 0.97. Nonetheless, in the rarely explored time domain, our analyses reveal a novel modality of relation between vibration generated at different heights of a structure and the associated height, which was explored in the frequency domain earlier in the literature with expensive sensors." @default.
• W3113221390 created "2020-12-21" @default.
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• W3113221390 date "2020-12-08" @default.
• W3113221390 modified "2023-09-26" @default.
• W3113221390 title "Let's Vibrate with Vibration: Augmenting Structural Engineering with Low-Cost Vibration Sensing." @default.
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