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

36 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

Fingerprint

Fuzzy inference
Accidents
Monitoring
Computer vision
Hazards
Managers
Acoustic waves

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Computer Science Applications

Cite this

@article{40e80388e07d4f669346ea500577621b,
title = "Vision-based object-centric safety assessment using fuzzy inference: Monitoring struck-by accidents with moving objects",
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.",
author = "Hongjo Kim and Kinam Kim and Hyoungkwan Kim",
year = "2016",
month = "7",
day = "1",
doi = "10.1061/(ASCE)CP.1943-5487.0000562",
language = "English",
volume = "30",
journal = "Journal of Computing in Civil Engineering",
issn = "0887-3801",
publisher = "American Society of Civil Engineers (ASCE)",
number = "4",

}

Vision-based object-centric safety assessment using fuzzy inference : Monitoring struck-by accidents with moving objects. / Kim, Hongjo; Kim, Kinam; Kim, Hyoungkwan.

In: Journal of Computing in Civil Engineering, Vol. 30, No. 4, 04015075, 01.07.2016.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Vision-based object-centric safety assessment using fuzzy inference

T2 - Monitoring struck-by accidents with moving objects

AU - Kim, Hongjo

AU - Kim, Kinam

AU - Kim, Hyoungkwan

PY - 2016/7/1

Y1 - 2016/7/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84975299383&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84975299383&partnerID=8YFLogxK

U2 - 10.1061/(ASCE)CP.1943-5487.0000562

DO - 10.1061/(ASCE)CP.1943-5487.0000562

M3 - Article

AN - SCOPUS:84975299383

VL - 30

JO - Journal of Computing in Civil Engineering

JF - Journal of Computing in Civil Engineering

SN - 0887-3801

IS - 4

M1 - 04015075

ER -