Vision-based object-centric safety assessment using fuzzy inference: Monitoring struck-by accidents with moving objects

Hongjo Kim, Kinam Kim, Hyoungkwan Kim

Research output: Contribution to journalArticle

55 Citations (Scopus)

Abstract

Due to the dynamic environment of construction sites, workers are continuously confronted with the potential for safety accidents. Although various safety guidelines have been developed, workers cannot always be aware of everything that occurs around them when they focus on their work on noisy and congested job sites. Therefore, it is difficult for workers to conform to guidelines to protect themselves when confronting dangerous situations. To address this safety issue, this paper presents an on-site safety-assessment system for monitoring struck-by accidents with moving entities based on computer vision and fuzzy inference. Computer vision is used to monitor a construction site and extract spatial information for each entity (workers and equipment). Next, fuzzy inference is used to assess the proper safety levels of each entity using spatial information. A safety level represents the potential hazard or the integrating danger that a person encounters at a particular moment. Struck-by accidents are selected as a target safety hazard for validation. The proposed system is expected to provide valuable information regarding worker safety represented as a numerical value. Using the record of safety levels, site managers can improve current working practices. For example, site managers can sound an alarm for workers when the safety level is too low.

Original languageEnglish
Article number04015075
JournalJournal of Computing in Civil Engineering
Volume30
Issue number4
DOIs
Publication statusPublished - 2016 Jul 1

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Computer Science Applications

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