Advanced monitoring of construction safety using UAS and positioning technologies

The high rate of fatalities in the construction domains is one of the major concerns of both practitioners and researchers. The dynamic nature of the construction, the limited number of safety managers, and the difficulty of visiting inaccessible, hard-to-reach, or unsafe locations are some of the factors that adversely affect the capability to properly and frequently monitoring construction sites and, therefore identify hazards. Unmanned aerial systems (UASs) and positioning technologies have become potential tools for enhancing safety-related tasks on construction jobsites. This study aims to develop, assess, and implement customized UASs and positioning sensors for enhancing safety monitoring and hazard identification process on construction jobsites. To accomplish this objective, an exploratory case study was carried out to compare safety managers' risk perception by using UAS-generated visual content and traditional-based visual content. Later, an ultrasound-based positioning system was developed and tested on real construction sites. The main objective of the system was to determine workers' position and calculating their hazard exposure time indoor, especially where UASs cannot operate for collecting visual data. Finally, two UASs were designed, developed, and tested using commercially available open-source software and hardware. The first UAS was equipped with a dualfrequency GNSS (L1/L2) and Post Processed Kinematic (PPK) technology in order to increase the quality and accuracy of the 3D visual representation of construction sites. A second UAS known as iSafeUAS was designed and tested to minimize the potential safety risks associated with UAS deployment for construction-safety related applications. The outcome of this research showed that the systematic use of both UASs and positioning technology on construction sites allows enhancing safety managers' risk perception, reduces time and efforts during the data collection process, increases the amount and quality of the information retrieved, and minimizes the risk associated with the data collection process.