
@article{ref1,
title="Real-time alarming, monitoring, and locating for non-hard-hat use in construction",
journal="Journal of construction engineering and management",
year="2019",
author="Zhang, Hong and Yan, Xuzhong and Li, Heng and Jin, Rui and Fu, HongFeng",
volume="145",
number="3",
pages="e1629-e1629",
abstract="Non-hard-hat use (NHU) is related to many construction accidents, so NHU inspection is crucial to safety management, in which automatic NHU monitoring plays an essential role. Existing computer vision-based NHU inspection methods lack capabilities in identifying workers and helping take real-time action. Previous sensor-based NHU inspection methods require direct skin contact, which would be uncomfortable for workers. In addition, previous sensor-based methods could be deceived by objects other than human heads and could not achieve real-time alarms. This study aims to address these problems by implementing real-time alarming, monitoring, and locating for NHU in construction based on sensor, mobile, web, and cloud techniques. A smart hard-hat system is developed using an Internet of Things (IoT)-based architecture including (1) a hard hat with an infrared beam detector and thermal infrared sensor for nonintrusive NHU detection; (2) radio-frequency identification (RFID) triggers for locating NHU with an average detection error of less than 10 cm; (3) a smartphone application for personalized warnings; (4) a web application for data visualization and alarms for managers; and (5) a cloud sever for data storage and retrieval. The proposed system enables both workers and managers to take timely actions against NHU. The system performance is evaluated in a laboratory test and validated in a field application. It is indicated that the proposed system is accurate and reliable, showing potential to promote safety inspection and supervision in construction.<p /> <p>Language: en</p>",
language="en",
issn="0733-9364",
doi="10.1061/(ASCE)CO.1943-7862.0001629",
url="http://dx.doi.org/10.1061/(ASCE)CO.1943-7862.0001629"
}