Real-time Locating System-enabled Digital Twin for Crane Operation Safety Monitoring on Construction Sites

Peisen Li, Jingda Xie, Jiyuchen Ding, Zhiheng Zhao (Corresponding Author), Wei Wu, George Q. Huang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Crane loads present a significant safety concern on construction sites. Numerous studies have employed the real-time locating system (RTLS) to identify crane load fall zones where crane loads may fall in the event of an accident. However, previous studies often assumed that the fall zone directly beneath the load was static and of a fixed size. In fact, the crane load fall zone is dynamic, varying with the movement of the crane jib and the geometric attribute of different crane loads. The dynamic identification of load fall zones to mitigate corresponding safety risks for on-site workers presents a complex challenge. In this paper, we design the RTLS-enabled digital twin for crane operation safety monitoring on construction sites for modular integrated construction (MiC). First, the improved algorithm is designed to dynamically identify the load fall zone associated with different prefabs. Second, we utilize an ultra-wideband (UWB) technology and time difference of arrival (TDoA) algorithm to pinpoint on-site workers in potential danger. Finally, safety warnings are provided to crane operators and onsite workers in potential danger zones to mitigate safety risks. Tests were conducted in a controlled laboratory environment to validate the proposed methodology. The results indicate that the system is effective in identifying dangerous zones, detecting worker proximity, and generating timely safety warnings, which can effectively mitigate safety risks on construction sites.

Original languageEnglish
Title of host publication2024 IEEE 20th International Conference on Automation Science and Engineering, CASE 2024
PublisherIEEE Computer Society
Pages2689-2696
Number of pages8
ISBN (Electronic)9798350358513
DOIs
Publication statusPublished - Aug 2024
Event20th IEEE International Conference on Automation Science and Engineering, CASE 2024 - Bari, Italy
Duration: 28 Aug 20241 Sept 2024

Publication series

NameIEEE International Conference on Automation Science and Engineering
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference20th IEEE International Conference on Automation Science and Engineering, CASE 2024
Country/TerritoryItaly
CityBari
Period28/08/241/09/24

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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