Real-time Rotational Obstacle Detection based Intelligent Safety Management for Construction Machines

초록

The number of industrial accidents has been recorded by construction cranes for a high proportion compared to other machines on construction sites. For this reason the technology for preventing collision between salvages and obstacles is strongly demanded. In this study, we propose an intelligent safety management method based on a rotational obstacle detection that detects obstacles around a crane by learning a private dataset acquired in an environment similar to an actual construction site. The rotational obstacle detection model of the proposed method is designed to more accurately predict obstacles around a crane using RGB video sequences images from the multi-domain dataset. It is composed of the real-time models for object detection, one of the typical onestage detectors, and the self attention distillation (SAD) method. In the experimental results, its performance of accuracy over than 70% mAP. This study can be applied not only to cranes but also to other machines for safety monitoring systems on various domain fields. © 2023 SPIE.

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