2024 Volume 80 Issue 19 Article ID: 24-19004
Video Dust Meter (VDM) is a newly developed video camera specialized for detecting floating dust, designed to monitor tunnel dust levels in construction. This study has developed an object detector using deep learning to automatically detect and count dust particles from video captured by the VDM. Laboratory experiments simulating dust-filled environment in tunnel construction were conducted to prepare image datasets for deep learning. YOLO v5 was used for object detection. Utilizing the developed YOLO dust particle detector, the VDM video of the laboratory dust experiment was analyzed to count the dust particles, and the results were compared to the reference measurements obtained by the Digital Dust Meter (LD-5R). As a result, the number of dust particles measured with the VDM and YOLO detector correlates highly with the measurements obtained by the reference Digital Dust Meter. The calibration coefficient between the two methods corresponds approximately to the ratio of the assessed air volumes by each method. It implies that the VDM can estimate the dust levels obtained by the Digital Dust Meter.
