Bird’S-Eye View Safety Monitoring for the Construction Top Under the Tower Crane

Abstract

The tower crane is involving more automated and intelligent operation procedure, and it is essential to protect the human workers on the workspace of construction top with Modular Integrated Construction (MiC) lifted from the bird’s-eye view. We present an AI-based automated safety monitoring system for tower crane, surveilling to shield the human operators on the construction top and avoid cranes’ collision. The system achieved a 3D data fusion for localization of humans and MiCs by integrating the captured information from camera and LiDAR. The state-of-the-art methods were explored and implemented into our proposed software pipeline coupled with the hardware and display systems. Furthermore, we conducted an analysis of the components in the pipeline to verify the accuracy and effectiveness of the involved methods. The display and visualization on the real site proved that our system can serve as a valuable safety monitoring toolkit on site.

Keywords: bird's-eye view, Deep Learning, data fusion, MiC lifting safety monitoring