Real-Time Alarming, Monitoring, and Locating for Non-Hard-Hat Use in Construction

TLDR

Non‑hard‑hat use is a major contributor to construction accidents, yet current computer‑vision and sensor‑based inspections fail to identify workers, provide real‑time alerts, or avoid contact discomfort. This study develops a real‑time, non‑intrusive system to alarm, monitor, and locate non‑hard‑hat use on construction sites. The system employs an IoT architecture comprising a hard hat equipped with infrared beam and thermal sensors, RFID triggers for sub‑10 cm location accuracy, a smartphone app for personalized warnings, a web dashboard for manager alerts, and cloud storage for data. Field validation shows the system accurately detects and locates non‑hard‑hat use, enabling timely corrective actions and demonstrating reliable performance that can enhance construction safety supervision.

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.