TY - JOUR
T1 - Automated hazardous area identification using laborers' actual and optimal routes
AU - Kim, Hyunsoo
AU - Lee, Hyun Soo
AU - Park, Moonseo
AU - Chung, Boo Young
AU - Hwang, Sungjoo
N1 - Funding Information:
This research was supported by a grant from the BIM R&D Program ( 14AUDP-C067809-2 ) funded by the Ministry of Land, Infrastructure, and Transport of the Korean government.
Publisher Copyright:
© 2016 Elsevier B.V. All rights reserved.
PY - 2016/5/1
Y1 - 2016/5/1
N2 - Approximately 20% of accidents in construction industry occur while workers are moving through a construction site. Current construction hazard identification mostly relies on safety managers' capabilities to detect hazards. Consequently, numerous hazards remain unidentified, and unidentified hazards mean that hazards are not included in the safety management process. To enhance the capability of hazard identification, this paper proposes an automated hazardous area identification model based on the deviation between the optimal route (shortest path)-which is determined by extracting nodes from objects in a building information model (BIM)- A nd the actual route of a laborer collected from the real-time location system (RTLS). The hazardous area identification framework consists of six DBs and three modules. The unidentified hazardous area identification module identifies potentially hazardous areas (PHAs) in laborers' paths. The filtering hazardous area module reduces the range of possible hazardous areas to improve the efficiency of safety management. The monitoring and output generation module provides reports including hazardous area information. The suggested model can identify a hazard automatically and decrease the time laborers are exposed to a hazard. This can help improve both the effectiveness of the hazard identification process and enhance the safety for laborers.
AB - Approximately 20% of accidents in construction industry occur while workers are moving through a construction site. Current construction hazard identification mostly relies on safety managers' capabilities to detect hazards. Consequently, numerous hazards remain unidentified, and unidentified hazards mean that hazards are not included in the safety management process. To enhance the capability of hazard identification, this paper proposes an automated hazardous area identification model based on the deviation between the optimal route (shortest path)-which is determined by extracting nodes from objects in a building information model (BIM)- A nd the actual route of a laborer collected from the real-time location system (RTLS). The hazardous area identification framework consists of six DBs and three modules. The unidentified hazardous area identification module identifies potentially hazardous areas (PHAs) in laborers' paths. The filtering hazardous area module reduces the range of possible hazardous areas to improve the efficiency of safety management. The monitoring and output generation module provides reports including hazardous area information. The suggested model can identify a hazard automatically and decrease the time laborers are exposed to a hazard. This can help improve both the effectiveness of the hazard identification process and enhance the safety for laborers.
KW - Automated data collection (ADC)
KW - Building information modeling (BIM)
KW - Hazard area identification
KW - Real-time locating system (RTLS)
KW - Safety management
UR - http://www.scopus.com/inward/record.url?scp=84959486631&partnerID=8YFLogxK
U2 - 10.1016/j.autcon.2016.01.006
DO - 10.1016/j.autcon.2016.01.006
M3 - Article
AN - SCOPUS:84959486631
SN - 0926-5805
VL - 65
SP - 21
EP - 32
JO - Automation in Construction
JF - Automation in Construction
ER -