TY - GEN
T1 - An integrated approach to capture construction workers' response towards safety alarms using wearable sensors and virtual reality
AU - Zou, Zhengbo
AU - Bernardes, Suzana Duran
AU - Kurkcu, Abdullah
AU - Ergan, Semiha
AU - Ozbay, Kaan
N1 - Publisher Copyright:
© EG-ICE 2020 Workshop on Intelligent Computing in Engineering, Proceedings. All rights reserved.
PY - 2020
Y1 - 2020
N2 - Despite the continuous efforts from federal and state agencies to improve safety at traffic work zones, incidents continue to occur, resulting in 675 fatalities in the U.S. during the last decade. Current safety measures at work zones, such as visual and audible alarms are ineffective due to the lack of calibration studies to evaluate the attention span of workers towards alarms, given variances in the alarm modality, frequency and duration. This study proposes an integrated approach combining virtual reality (VR) and wearable sensors to capture data regarding workers' behaviors towards safety alarms when workers are exposed to simulated dangerous situations in VR. This dataset is needed to understand the relationships between workers' responses (i.e., react or dismiss) and the characteristics of the received alarms (i.e., modality, frequency, and duration). The proposed approach was implemented on an urban intersection from a real-world work zone in New York City for user studies.
AB - Despite the continuous efforts from federal and state agencies to improve safety at traffic work zones, incidents continue to occur, resulting in 675 fatalities in the U.S. during the last decade. Current safety measures at work zones, such as visual and audible alarms are ineffective due to the lack of calibration studies to evaluate the attention span of workers towards alarms, given variances in the alarm modality, frequency and duration. This study proposes an integrated approach combining virtual reality (VR) and wearable sensors to capture data regarding workers' behaviors towards safety alarms when workers are exposed to simulated dangerous situations in VR. This dataset is needed to understand the relationships between workers' responses (i.e., react or dismiss) and the characteristics of the received alarms (i.e., modality, frequency, and duration). The proposed approach was implemented on an urban intersection from a real-world work zone in New York City for user studies.
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M3 - Conference contribution
AN - SCOPUS:85091050196
T3 - EG-ICE 2020 Workshop on Intelligent Computing in Engineering, Proceedings
SP - 164
EP - 174
BT - EG-ICE 2020 Workshop on Intelligent Computing in Engineering, Proceedings
A2 - Ungureanu, Lucian-Constantin
A2 - Hartmann, Timo
PB - Universitatsverlag der TU Berlin
T2 - 27th EG-ICE International Workshop on Intelligent Computing in Engineering 2020
Y2 - 1 July 2020 through 4 July 2020
ER -