Deep learning-based construction activity classification

Construction activities often produce excessive and prolonged vibrations that can be detrimental to adjacent infrastructure, equipment, as well as people. To mitigate the negative effects of construction-induced vibrations, vibration monitoring is usually implemented to analyse the impacts of the vi...

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Bibliographic Details
Main Author: Lian, Si Hui
Other Authors: Fu Yuguang
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
Subjects:
CNN
Online Access:https://hdl.handle.net/10356/177290
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1772902024-05-24T15:34:55Z Deep learning-based construction activity classification Lian, Si Hui Fu Yuguang School of Civil and Environmental Engineering yuguang.fu@ntu.edu.sg Engineering Civil engineering Machine learning Deep learning CNN Construction activities often produce excessive and prolonged vibrations that can be detrimental to adjacent infrastructure, equipment, as well as people. To mitigate the negative effects of construction-induced vibrations, vibration monitoring is usually implemented to analyse the impacts of the vibrations. However, these vibration data collected were mostly not fully utilised due to the lack of information such as labelling of data. Therefore, this study aims to collect vibration data on various construction activities followed by developing a deep learning (DL) algorithm to recognise the different construction activities. The classification of construction activity was performed by adopting a convolutional neural network. Bachelor's degree 2024-05-24T07:20:52Z 2024-05-24T07:20:52Z 2024 Final Year Project (FYP) Lian, S. H. (2024). Deep learning-based construction activity classification. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/177290 https://hdl.handle.net/10356/177290 en CT-02 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
Civil engineering
Machine learning
Deep learning
CNN
spellingShingle Engineering
Civil engineering
Machine learning
Deep learning
CNN
Lian, Si Hui
Deep learning-based construction activity classification
description Construction activities often produce excessive and prolonged vibrations that can be detrimental to adjacent infrastructure, equipment, as well as people. To mitigate the negative effects of construction-induced vibrations, vibration monitoring is usually implemented to analyse the impacts of the vibrations. However, these vibration data collected were mostly not fully utilised due to the lack of information such as labelling of data. Therefore, this study aims to collect vibration data on various construction activities followed by developing a deep learning (DL) algorithm to recognise the different construction activities. The classification of construction activity was performed by adopting a convolutional neural network.
author2 Fu Yuguang
author_facet Fu Yuguang
Lian, Si Hui
format Final Year Project
author Lian, Si Hui
author_sort Lian, Si Hui
title Deep learning-based construction activity classification
title_short Deep learning-based construction activity classification
title_full Deep learning-based construction activity classification
title_fullStr Deep learning-based construction activity classification
title_full_unstemmed Deep learning-based construction activity classification
title_sort deep learning-based construction activity classification
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/177290
_version_ 1800916330656825344