4D point cloud-based spatial-temporal semantic registration for monitoring mobile crane construction activities

Abstract

<p> Existing construction activity-monitoring technologies, such as CCTV cameras and IoT devices, have limitations, such as lack of depth information, 3D measurement errors, or wireless signal vulnerability. The limitations are particularly problematic for activities related to mobile cranes due to their high mobility and flexibility. This paper presents a 4D point cloud (4DPC)-based spatial-temporal semantic registration method to overcome the limitations. The proposed method integrates spatial-temporal semantic registration into process site 4DPC with as-designed BIM semantics. Results from a one-hour on-site experiment demonstrated that the proposed method achieved 99.93-100% F1 accuracy in detecting BIM objects, and high resolution (centimeter-second granularity) of the trajectories of hoisting activities. This paper offers a twofold contribution. First, spatial-temporal semantic registration represents an innovative approach to 4D point cloud (4DPC) processing. Secondly, the hoisting activities are comprehensively analyzed based on semantic registration, which can improve safety and productivity monitoring for smarter construction in the future. <br></p>