TY - GEN
T1 - Automated Construction Site Safety Monitoring Using Preidentified Static and Dynamic Hazard Zones
AU - Hong, Kepeng
AU - Teizer, Jochen
N1 - Publisher Copyright:
© 2024 ISARC. All Rights Reserved.
PY - 2024
Y1 - 2024
N2 - Ensuring workers’ safety at construction sites is complicated as protective measures often involve the tasks of planning, monitoring, and mitigation at the same time. Despite traditional methods during the pre-construction and construction phases that require time-consuming and manual efforts, poor risk assessment and situational awareness can easily lead to unplanned mishaps in detecting and eliminating risk. Semi-automated rule-based risk assessment approaches as they predominantly exist in research (ref. SafeConAI) are capable of designing out known hazards before they appear in the workplace. These, however, tend not to be interoperable with other emerging technology tasked to monitor how well safety is practiced on the construction site. This paper presents a method for enhanced safety incident analysis by fusing preidentified hazard zones that remain in construction schedules (after SafeConAI has been applied to a 4D BIM) with high-precision trajectory data (using RTK-GNSS) of pedestrian workers and heavy construction equipment. A real-life case study validates the method’s feasibility yielding, aside from basic statistical spatiotemporal counting of incident numbers and precise locations between the pedestrian workforce and construction equipment, also new insights into the right size of the so-defined protective safety envelopes that should surround the construction machinery. These promising results still require further investigation into the practical applicability, for example, testing the effectiveness of sharing the detailed personalized feedback that becomes now available.
AB - Ensuring workers’ safety at construction sites is complicated as protective measures often involve the tasks of planning, monitoring, and mitigation at the same time. Despite traditional methods during the pre-construction and construction phases that require time-consuming and manual efforts, poor risk assessment and situational awareness can easily lead to unplanned mishaps in detecting and eliminating risk. Semi-automated rule-based risk assessment approaches as they predominantly exist in research (ref. SafeConAI) are capable of designing out known hazards before they appear in the workplace. These, however, tend not to be interoperable with other emerging technology tasked to monitor how well safety is practiced on the construction site. This paper presents a method for enhanced safety incident analysis by fusing preidentified hazard zones that remain in construction schedules (after SafeConAI has been applied to a 4D BIM) with high-precision trajectory data (using RTK-GNSS) of pedestrian workers and heavy construction equipment. A real-life case study validates the method’s feasibility yielding, aside from basic statistical spatiotemporal counting of incident numbers and precise locations between the pedestrian workforce and construction equipment, also new insights into the right size of the so-defined protective safety envelopes that should surround the construction machinery. These promising results still require further investigation into the practical applicability, for example, testing the effectiveness of sharing the detailed personalized feedback that becomes now available.
KW - 4D BIM
KW - Construction safety planning
KW - Hazards
KW - Pedestrian workers
KW - Protective equipment envelopes
KW - Safety risk assessment
KW - RTK-GNSS location tracking
U2 - 10.22260/ISARC2024/0051
DO - 10.22260/ISARC2024/0051
M3 - Article in proceedings
AN - SCOPUS:85199643012
T3 - Proceedings of the ISARC
SP - 388
EP - 395
BT - Proceedings of the 41st International Symposium on Automation and Robotics in Construction (ISARC 2024)
PB - International Association for Automation and Robotics in Construction (IAARC)
T2 - 41<sup>st</sup> International Symposium on Automation and Robotics in Construction
Y2 - 3 June 2024 through 7 June 2024
ER -