Study on Precise Identification of Unsafe Behaviors of Construction Workers Based on Multi-source Data Fusion |
| Yunjie Xiao Zhe Liu Wenhui Liu |
| 1.Tianjin Dongfang Tairui Technology Co., Ltd., Tianjin 300171, China；2.Tianjin Tianke Work Safety Science Research Institute Co., Ltd., Tianjin 300171, China |
Abstract : In the field of building construction, unsafe behaviors of construction workers are a critical factor contributing to safety accidents. This paper delves into relevant key technologies based on multi-source data fusion technology and proposes a precise identification method for unsafe behaviors of construction workers through innovative practices such as constructing a fused data acquisition system, establishing an intelligent identification and early warning system, and implementing model dynamic optimization strategies. This method contributes to enhancing the accuracy and real-time performance of unsafe behavior identification.
Keywords Multi-source data fusion; Construction workers; Intelligent early warning; Model optimization
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References
[1] Fan Bingqian, Dong Bingyu, Wang Biao, et al. Unsafe behavior identification and application of metro construction workers based on deep learning [J]. China Safety Science Journal, 2023, 33(01): 41-47.
[2] Li Zhifeng. Analysis and control of high-risk operations in the construction of natural gas long-distance pipelines [J]. Chemical Enterprise Management, 2022, (05): 86-88.
[3] Li Junting, Zheng Mingzhu, Sai Yunxiu. Simulation study on intervention strategies for unsafe ehaviors of construction workers [J]. Industrial Engineering, 2021, 24(01): 111-116.
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Conflict of Interest
The author declares no conflict of interest.
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