期刊
AUTOMATION IN CONSTRUCTION
卷 158, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.autcon.2023.105195
关键词
Construction equipment; Tunnel construction; Activity recognition; Multimodal; Audio-visual model
This study introduces a contextual audio-visual approach to recognize multi-equipment activities in tunnel construction sites, improving monitoring effectiveness. Tested against real-world operation data, the model achieved remarkable results, emphasizing the potential of contextual multimodal models in enhancing operational efficiency in complex construction sites.
In order to accurately track progress and improve efficiency in complex construction projects, it's important to effectively monitor individual tasks and measure the time taken to complete a cycle of tasks. Tunnel construction involves a variety of activities, where multiple pieces of equipment are engaged in different actions that occur simultaneously or sequentially during a single activity. This study introduces a contextual audio-visual (multimodal) approach to better recognize multi-equipment activities in a tunnel construction site for monitoring purposes. By incorporating both audio and visual data, and by integrating both spatial and cyclical temporal contexts, the model accurately recognizes the activity being performed by multiple pieces of equipment more often than single-mode models. Tested against real-world operation data, the model achieved a remarkable Fscore of 96.3% in recognizing construction activities, demonstrating its superiority over traditional methods in scenarios involving multiple, simultaneously operating pieces of equipment. The results emphasize the potential of contextual multimodal models in enhancing operational efficiency in complex construction sites.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据