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    On-Site Construction Worker Activity Monitoring Using Deep Learning 

    Source: Journal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 004:;page 04026040-1
    Author(s): Monfared, Ehsan; Alipouri, Yaghoub
    Publisher: American Society of Civil Engineers
    Abstract: AbstractLow productivity in the construction industry compared with other sectors is a longstanding concern. Traditionally, managers have relied on manual sampling of worker activities by monitoring task types and durations ...
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    Construction Labor Activity Recognition via an IMU-Implemented Wristband 

    Source: Journal of Construction Engineering and Management:;2025:;Volume ( 151 ):;issue: 011:;page 04025182-1
    Author(s): Alipouri, Yaghoub; Bokharaeian, Amirhossein; Monfared, Ehsan
    Publisher: American Society of Civil Engineers
    Abstract: AbstractHuman labor is a pivotal element in determining project costs and overall success within the construction industry, necessitating robust monitoring of workers’ productivity, well-being, and the cultivation of a ...
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