A THEORETICAL CONSTRUCT FOR PROGRESSIVE CONSTRUCTION SITE SAFETY IMPLEMENTING SITUATIONAL AWARENESS IN UNMANNED AIRCRAFT SYSTEMS TO IMPROVE DECISION-MAKING AND SAFETY

摘要

As unmanned aerial systems (UAS) become more prevalent tools for providing construction professionals with data used to manage the construction process, they may also provide great promise to positively impact jobsite safety. With their organic capability to move quickly and access difficult areas of the jobsite, their real-time remote sensing capabilities can provide greater degrees of jobsite Level 2 Situation Awareness (SA). SA improves the decision-making and performance of the human jobsite safety manager and construction personnel in complex, dynamic environments by enhancing ambient awareness, an essential attribute for jobsite safety. Unfortunately, this complex environment may also make filtering and organizing information in a timely and accurate manner difficult for the jobsite safety manager. This results in less than optimal decisions. This paper discusses the embodiment of deep learning neural network imagery processing for Level 2 SA enabled by the UAS to enhance decision-making in construction site safety management.