4D POINT CLOUD (4DPC)-DRIVEN REAL-TIME MONITORING OF CONSTRUCTION MOBILE CRANES

Abstract

Mobile cranes are essential equipment in construction sites due to their high flexibility and mobility. However, the existing sensing or monitoring methods have limitations in monitoring mobile cranes on sites. Recently, the advent of 4D point cloud (4DPC) technology with a unique spatial-temporal data structure has shown potential in addressing these issues. In this paper, we present a 4DPC monitoring approach, which includes a set of prototype devices and a rule-based object detection method. We conducted a proof-of-concept test to monitor the hoisting process of two H-beams in a footbridge construction project. The rule-based object detection method successfully detected the target beams in the collected six-hour 4DPC data. In the future, we expect more efficient and robust 4DPC sensing devices and processing methods for proactive crane motion prediction and optimization in a time-dynamic site environment.