Activity classification using accelerometers and machine learning for complex construction worker activities

Automated Construction worker activity classification has the potential to not only benefit the worker performance in terms of productivity and safety, but also the overall project management and control. The activity-level knowledge and indicators that can be extracted from this process may support...

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Veröffentlicht in:	Journal of Building Engineering Jg. 35; S. 102001
Hauptverfasser:	Sanhudo, Luís, Calvetti, Diego, Martins, João Poças, Ramos, Nuno M.M., Mêda, Pedro, Gonçalves, Miguel Chichorro, Sousa, Hipólito
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.03.2021
Schlagworte:	Activity classification Construction workers Productivity analysis Supervised machine learning Wearable accelerometers Supervised machine learning Productivity analysis Activity classification Wearable accelerometers Construction workers
ISSN:	2352-7102, 2352-7102
Online-Zugang:	Volltext
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