Real-time alarming, monitoring, and locating for non-hard-hat use in construction

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.