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Proximity Warning and Excavator Control System for Prevention of Collision Accidents

Author

Listed:
  • Byung-Wan Jo

    (Department of Civil and Environmental Engineering, Hanyang University, Seoul 04763, Korea)

  • Yun-Sung Lee

    (Department of Civil and Environmental Engineering, Hanyang University, Seoul 04763, Korea)

  • Jung-Hoon Kim

    (Department of Civil and Environmental Engineering, Hanyang University, Seoul 04763, Korea)

  • Do-Keun Kim

    (Department of Civil and Environmental Engineering, Hanyang University, Seoul 04763, Korea)

  • Pyung-Ho Choi

    (Research and Development Center, Youngshine, Gyeonggi-do 13487, Korea)

Abstract

Construction is a hazardous industry in which accidents occur frequently. Occupational accidents at construction sites are a serious public health issue in Korea. Construction site conditions often create dangerous situations by requiring workers and heavy equipment to work in close proximity to each other. In 2015, approximately 11% (46) of the 437 occupational fatalities in the construction industry in Korea resulted from workers colliding with objects or equipment. In this paper, we present a proximity warning system developed to address this issue and enhance safety at construction sites. The proposed technology functions in real time to alert workers and equipment operators of hazardous proximity situations. Also, when the radio frequency identification (RFID) sensor detects an approaching worker, the main board instantly shuts down the excavator for the prevention of accident. This system contains an RFID tag, RFID reader, alarm device, camera, a display device (the Around View Monitor), and excavator control technology. A field test demonstrated successful performance of the proposed system. It is widely applicable in small construction fields alongside excavators and other equipment because this system does not require additional communication infrastructure, such as servers.

Suggested Citation

  • Byung-Wan Jo & Yun-Sung Lee & Jung-Hoon Kim & Do-Keun Kim & Pyung-Ho Choi, 2017. "Proximity Warning and Excavator Control System for Prevention of Collision Accidents," Sustainability, MDPI, vol. 9(8), pages 1-20, August.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:8:p:1488-:d:109215
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    References listed on IDEAS

    as
    1. Eric Daniel Marks & Jochen Teizer, 2013. "Method for testing proximity detection and alert technology for safe construction equipment operation," Construction Management and Economics, Taylor & Francis Journals, vol. 31(6), pages 636-646, June.
    2. Byung Wan Jo & Yun Sung Lee & Jung Hoon Kim & Rana Muhammad Asad Khan, 2017. "Trend Analysis of Construction Industrial Accidents in Korea from 2011 to 2015," Sustainability, MDPI, vol. 9(8), pages 1-12, July.
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    Cited by:

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    2. Bon-Gang Hwang & Ming Shan, 2018. "Management Strategies and Innovations: Important Roles to Sustainable Construction," Sustainability, MDPI, vol. 10(3), pages 1-3, February.
    3. Jieun Baek & Yosoon Choi, 2020. "Smart Glasses-Based Personnel Proximity Warning System for Improving Pedestrian Safety in Construction and Mining Sites," IJERPH, MDPI, vol. 17(4), pages 1-15, February.
    4. Daeho Kim & Ankit Goyal & SangHyun Lee & Vineet R. Kamat & Meiyin Liu, 2024. "Single-Shot Visual Relationship Detection for the Accurate Identification of Contact-Driven Hazards in Sustainable Digitized Construction," Sustainability, MDPI, vol. 16(12), pages 1-16, June.
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    6. Ahmed Khairadeen Ali & One Jae Lee & Doyeop Lee & Chansik Park, 2021. "Remote Indoor Construction Progress Monitoring Using Extended Reality," Sustainability, MDPI, vol. 13(4), pages 1-23, February.
    7. Danilo Monarca & Pierluigi Rossi & Riccardo Alemanno & Filippo Cossio & Paolo Nepa & Andrea Motroni & Roberto Gabbrielli & Marco Pirozzi & Carla Console & Massimo Cecchini, 2022. "Autonomous Vehicles Management in Agriculture with Bluetooth Low Energy (BLE) and Passive Radio Frequency Identification (RFID) for Obstacle Avoidance," Sustainability, MDPI, vol. 14(15), pages 1-13, August.
    8. Ali Noudoostbeni & Kiran Kaur & Hashem Salarzadeh Jenatabadi, 2018. "A Comparison of Structural Equation Modeling Approaches with DeLone & McLean’s Model: A Case Study of Radio-Frequency Identification User Satisfaction in Malaysian University Libraries," Sustainability, MDPI, vol. 10(7), pages 1-16, July.

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