The rise of digitalization in constructions: State-of-the-art in the use of sensing technology for advanced building-assistance systems

The construction sector is traditionally affected by on-site errors that significantly impact both budget and schedule. To minimize these errors, researchers have long hypothesized the development of AR-enriched 4D models that can guide workers on components deployment, assembly procedures, and work progress. Such systems have recently been referred to as Advanced Building-Assistance Systems (ABAS). However, despite the clear need to reduce the on-site errors, an ABAS has not been implemented and tested yet. This is partially due to a limited comprehension of the current wealth of available sensing technologies in the construction industry. To bridge the current knowledge gap, this paper evaluates the capabilities of current use of sensing technologies for objects identification, location, and orientation. This study employs and illustrates a systematic methodology to select according to eight criteria and analyzed in three level the literature on the field to ensure comprehensive coverage of the topic. The findings highlight both the capabilities and constraints of current sensing technologies, while also providing insight into potential future opportunities for integrating advanced tracking and identification systems in the built environment.