CNN model for mining safety hazard data from a construction site

LIN Peng; WEI Pengcheng; FAN Qixiang; CHEN Wenqi

doi:10.16511/j.cnki.qhdxxb.2019.26.008

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Journal of Tsinghua University(Science and Technology) ›› 2019, Vol. 59 ›› Issue (8) : 628-634. DOI: 10.16511/j.cnki.qhdxxb.2019.26.008

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CNN model for mining safety hazard data from a construction site

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Abstract

A convolutional neural network model was used to mine typical safety hazard data from an infrastructure construction site for site intelligent safety control. Safety hazard data from a hydropower station during construction was analyzed to show the typical safety hazard data characteristics. The learning and mining used a convolution neural network (CNN) with the convolution layer, pooling layer, fully connected layer and training and testing processes defined here. The data mining and learning improves the safety flat-closed loop management safety for the construction site for intelligent safety management. The method then automatically identifies typical safety hazards for construction sites. The results provide guidance for automatic classification and analysis of safety hazards for a construction project.

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intelligent safety management / safety hazards / data learning and mining / convolutional neural networks

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LIN Peng, WEI Pengcheng, FAN Qixiang, CHEN Wenqi. CNN model for mining safety hazard data from a construction site[J]. Journal of Tsinghua University(Science and Technology). 2019, 59(8): 628-634 https://doi.org/10.16511/j.cnki.qhdxxb.2019.26.008

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