International conference on construction engineering and project management (국제학술발표논문집)

  • 2024.07a
  • /
  • Pages.1096-1102
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  • 2024
  • /
  • 2508-9048(eISSN)
Korea Institute of Construction Engineering and Management (한국건설관리학회)
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Intelligent Hoist Control Based on Computer Vision

  • Seokhyeon Jin (Department of Architecture & Building Sciences, Chung-Ang University) ;
  • Dabin Lee (Department of Architecture & Building Sciences, Chung-Ang University) ;
  • Dohyeong Kim (Department of Architecture & Building Sciences, Chung-Ang University) ;
  • Chansik Park (Department of Architecture & Building Sciences, Chung-Ang University) ;
  • Dongmin Lee (Department of Architecture & Building Sciences, Chung-Ang University)
  • Published : 2024.07.29
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Abstract

Construction hoists are essential equipment for vertical lifting of workers and materials on construction sites, and their efficient operation significantly impacts the success of construction projects. To optimize hoist operation, it is crucial to accurately understand the call situation on each floor (i.e., the external waiting state) and the internal state of the hoist. This study aims to use object detection technology to monitor the status of workers and materials waiting on each floor, as well as the boarding state inside the hoist in real-time. Subsequently, by utilizing the real-time gathered information, a model was developed to reduce the number of stops, thereby demonstrating the potential of object detection technology in reducing the hoist's transportation time. The research results show that it is possible to determine the number of workers, the types of materials, and the quantity of materials to board the hoist using object detection, and to derive an optimized route. Consequently, it demonstrates that the use of object detection can reduce the transportation time of the hoist, thereby improving its operational efficiency.

Keywords

Acknowledgement

This research was conducted with the support of the "National R&D Project for Smart Construction Technology (No.RS-2020-KA156291)" funded by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land, Infrastructure and Transport, and managed by the Korea Expressway Corporation. Additionally, this research was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT)(No. RS-2023-00217322 and No. NRF-2022R1A2B5B02002553).

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