International conference on construction engineering and project management (국제학술발표논문집)

  • 2024.07a
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  • Pages.629-636
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  • 2024
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  • 2508-9048(eISSN)
Korea Institute of Construction Engineering and Management (한국건설관리학회)
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Enhancing On-Site Construction Machinery Handling through 3D Spatial Gesture-Based Trajectory Interpreter Modeling

  • Du LI (Department of Building and Real Estate, Faculty of Construction and Environment, The Hong Kong Polytechnic University) ;
  • Ying WANG (Department of Building and Real Estate, Faculty of Construction and Environment, The Hong Kong Polytechnic University) ;
  • Hung-Lin CHI (Department of Building and Real Estate, Faculty of Construction and Environment, The Hong Kong Polytechnic University)
  • Published : 2024.07.29
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Abstract

In construction projects, the safety and productivity of machinery operations are of paramount importance. Contemporary research and industry endeavors predominantly concentrate on equipping machine operators with sensory information and establishing a comprehensive situation-aware operating environment, such as virtual reality-based machine manipulation training. However, significant limitations exist in direct information exchange and processing by on-site personnel. Notably, research on analyzing communication patterns in construction machinery operations remains scarce despite its critical role in preventing hazardous instructions/actions and enhancing machinery work efficiency. Thus, this research aims to (1) develop a novel interpreter modeling system predicated on millimeter-wave radar technology and (2) select the crane as an illustration to investigate the potential applications of this emerging communication paradigm during construction machinery operations. In this investigation, a spatial gesture signal interpreter was devised specifically for machine operators and signalers to augment the quality of communication during the execution of spatial localization tasks. Corresponding limitations that will be encountered in current communication systems were also addressed. This research uses a 60 GHz millimeter wave radar as a gesture trajectory detector, with the benefits of portability and robustness. Its millimeter-level precision enables the capture of highly accurate micro-gestures. The research constructs a novel 3D Spatial Gesture-based Trajectory Modeling system, which will be compared with traditional communication models in future research stages.

Keywords

Acknowledgement

The authors would like to thank the Research Grants Council, Hong Kong, for their funding support under the General Research Fund (PolyU 25221519).

References

  1. Bernold E. Leonhard, Lorenc J. Steven and Luces Erick (1997). "On-Line Assistance for Crane Operators" Journal of Computing in Civil Engineering, 11(4),248-259.
  2. Chen, J., Chi, H. L., Du, Q., & Wu, P. (2022). "Investigation of Operational Concerns of Construction Crane Operators: An Approach Integrating Factor Clustering and Prioritization". Journal of Management in Engineering, 38(4), Article 04022020.
  3. Raviv, G., Fishbain, B., & Shapira, A. (2017). "Analyzing Risk Factors in Crane-related Near-miss and Accident Reports", Safety Science, 91, 192-205.
  4. Tam, W. Y., & Fung, W. H. (2011). "Tower Crane Safety in the Construction Industry: A Hong Kong Study", Safety Science, 49(2), 208-215.
  5. Zekavat, Payam & Bernold, Leonhard. (2014). "Embedded Wireless Communication Platform Addresses Crane Safety and Efficiency". 309-318. 10.1061/9780784413517.032.
  6. Choi, B., Hwang, S., & Lee, S. (2017). "What drives construction workers' acceptance of wearable technologies in the workplace?: Indoor localization and wearable health devices for occupational safety and health". Automation in Construction, 84, 31-41.
  7. Mansoor, A., Liu, S., Ali, G.M., Bouferguene, A., & Al-Hussein, M. (2020). "Conceptual Framework for Safety Improvement in Mobile Cranes".
  8. K. A. Smith, C. Csech, D. Murdoch and G. Shaker, "Gesture recognition using mm-wave sensor for human-car interface", IEEE Sens. Lett., vol. 2, no. 2, pp. 1-4, Jun. 2018.
  9. DONG Lianfei, Ma Zhixiong, ZHU Xichan. "Dynamic Gesture Recognition Network Based on Vehicular Millimeter Wave Radar[J]". Transactions of Beijing institute of Technology, 2023, 43(5):493-498.
  10. ISO 16715:2014 "Cranes - Hand signals used with cranes"
  11. Cheng, Tao & Teizer, Jochen. (2013). "Modeling Tower Crane Operator Visibility to Minimize the Risk of Limited Situational Awareness". Journal of Computing in Civil Engineering. 28. 10.1061/(ASCE)CP.1943-5487.0000282.
  12. Zekavat, P. R., & Bernold, L. (2014). "Embedded Wireless communication platform addresses crane safety and efficiency". In Construction Research Congress 2014: Construction in a Global Network (pp. 309-318).
  13. Everett J G, Slocum A H. "CRANIUM: Device for improving crane productivity and safety[J]". Journal of construction engineering and management, 1993, 119(1): 23-39.