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Dynamic Collision Alert System for Collaboration of Construction Equipment and Workers

Auteur(s): ORCID
ORCID

Médium: article de revue
Langue(s): anglais
Publié dans: Buildings, , n. 1, v. 15
Page(s): 110
DOI: 10.3390/buildings15010110
Abstrait:

The construction industry is considered one of the most hazardous industries. The accidents associated with construction equipment are a leading cause of fatalities in the U.S., with one-quarter of all fatalities in the construction industry due to equipment-related incidents, including collisions, struck-by events, and rollovers. While close collaboration among multiple equipment and humans is common, conventional collision alert mechanisms for equipment usually rely on distance sensors with static thresholds, often resulting in too many false alarms, causing drivers’ ignorance. Considering the collaborative operation scenario, this research proposes and develops a dynamic-threshold alert system by recognizing hazardous events based on the types of nearby objects with their orientation or postures and their distances to the system carrier equipment based on image-based recognition and Sim2Real techniques. Two experiments were conducted, and the results show that the system successfully reduced a large number of false near-collision alarms for the collaboration scenarios. Although the accuracy of object recognition and image-based distance estimation is feasible for practical use, it is also easily degraded in the self-obstruction scenario or for equipment with large and movable parts due to incorrect recognition of the bounding boxes of the target objects.

Copyright: © 2024 by the authors; licensee MDPI, Basel, Switzerland.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10810294
  • Publié(e) le:
    17.01.2025
  • Modifié(e) le:
    17.01.2025
 
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