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Computer Vision-Based Monitoring Framework for Forklift Safety at Construction Site

  • Muhammad Sibtain Abbas
  • Aqsa Sabir
  • Nasrullah Khan
  • Syed Farhan Alam Zaidi
  • Rahat Hussain
  • Jaehun Yang
  • Chansik Park

Efficient forklift operation is critical for construction site safety and project progress; yet, the construction industry deals with recurrent issues, including unauthorized forklift operation, operator drowsiness, visibility challenges, blind spots, and load placement errors. This paper introduces the "iSafe ForkLift," a comprehensive safety framework powered by computer vision, specifically designed to tackle these multifaceted safety challenges associated with forklift operations. The framework provides an array of integrated solutions, encompassing facial recognition for authorization, anomaly detection for behavior monitoring, stereo cameras for improved visibility, blind spot solutions, and load placement monitoring. Aligned with OSHA safety standards, it offers opportunities for enhanced forklift safety by addressing a broad spectrum of potential risks within a single, efficient framework. Systematically addressing multiple safety risks within this unified framework significantly elevates overall safety. Future studies should prioritize enhancing technology by merging computer vision with IoT to boost precision and safety, especially on challenging terrains, thereby elevating construction industry standards' reliability

  • Keywords:
  • Forklift operations,
  • Computer vision,
  • Safety framework,
  • Operator drowsiness,
  • Visibility challenges,
  • OSHA standards,
  • Regulatory compliance,
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Muhammad Sibtain Abbas

Chung Ang University, Korea (the Republic of)

Aqsa Sabir

Chung Ang University, Korea (the Republic of) - ORCID: 0009-0006-5459-909X

Nasrullah Khan

Chung Ang University, Korea (the Republic of)

Syed Farhan Alam Zaidi

Chung Ang University, Korea (the Republic of) - ORCID: 0000-0003-2257-290X

Rahat Hussain

Chung Ang University, Korea (the Republic of) - ORCID: 0000-0002-6909-5189

Jaehun Yang

Chung Ang University, Korea (the Republic of) - ORCID: 0000-0002-8192-340X

Chansik Park

Chung Ang University, Korea (the Republic of) - ORCID: 0000-0003-2256-300X

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  9. OSHA. (2023a). Accident Search Results. https://www.osha.gov/ords/imis/accidentsearch.search?sic=&sicgroup=&naics=&acc_description=&acc_abstract=&acc_keyword=forklift&inspnr=&fatal=&officetype=All&office=All&startmonth=07&startday=17&startyear=2024&endmonth=07&endday=17&endyear=2018&keyword_lis
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  11. Shete, R. G., Kakade, S. K., & Dhanvijay, M. (2021). A Blind-spot Assistance for Forklift using Ultrasonic Sensor. 2021 IEEE International Conference on Technology, Research, and Innovation for Betterment of Society, TRIBES 2021, 1–4. DOI: 10.1109/TRIBES52498.2021.9751672
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  • Publication Year: 2023
  • Pages: 676-682

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  • Publication Year: 2023

Chapter Information

Chapter Title

Computer Vision-Based Monitoring Framework for Forklift Safety at Construction Site

Authors

Muhammad Sibtain Abbas, Aqsa Sabir, Nasrullah Khan, Syed Farhan Alam Zaidi, Rahat Hussain, Jaehun Yang, Chansik Park

DOI

10.36253/979-12-215-0289-3.67

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Bibliographic Information

Book Title

CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality

Book Subtitle

Managing the Digital Transformation of Construction Industry

Editors

Pietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Publisher Name

Firenze University Press

DOI

10.36253/979-12-215-0289-3

eISBN (pdf)

979-12-215-0289-3

eISBN (xml)

979-12-215-0257-2

Series Title

Proceedings e report

Series ISSN

2704-601X

Series E-ISSN

2704-5846

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