With the rapid advancement of Unmanned Aerial Vehicle (UAV) technologies in recent years, their uses have been increasingly adopted in the architecture, engineering, and construction industries. To satisfy the needs of various types of construction projects, a considerable amount of research work has been performed to implement and refine the operations, safety, and accuracy of UAVs. This paper presents the findings of a comprehensive literature review that focuses on UAV research in construction management during the timeframe of 2016 to 2021. A total of 95 papers were identified and collected from a list of 21 relevant journals and conference proceedings, and were then categorized by their research topic, sensor types, and targeted structures. The results of 47 exemplary studies were reported in two categories, namely UAV uses and construction uses. The research topics identified for UAV uses include algorithm, applications, operations, framework, and training, while research topics identified for construction use include inspection, surveying, safety, and monitoring. The connection between the research topics, sensor types, targeted structures, and other advanced technologies were also discussed. This paper summarizes the current results of UAV research in construction management, reviews the methodology, benefits, and limitations of the reviewed literature, and provides valuable knowledge for the future trend of UAV applications in the civil, infrastructure, and construction industries.

This paper presents a time- and cost-efficient method for the management of construction and demolition (C&D) debris at construction sites, demolition jobsites, and illegal C&D waste dumping sites. The developed method integrates various drone, deep learning, and geographic information system (GIS) technologies, including C&D debris drone scanning, 3D reconstruction with structure from motion (SfM), image segmentation with fully convolutional network (FCN), and C&D debris information management with georeferenced 2D and 3D as-built. Experiments and parameter analysis led us to conclude that (1) drone photogrammetry using top- and side-view images is effective in the 3D reconstruction of C&D debris (stockpiles); (2) FCNs are effective in C&D debris extraction with point cloud-generated RGB orthoimages with a high intersection over union (IoU) value of 0.9 for concrete debris; and (3) using FCN-generated pixelwise label images, point cloud-converted elevation data for projected area, and volume measurements of C&D debris is both robust and accurate. The developed automatic method provides quantitative and geographic information to support city governments in intelligent information management of C&D debris.

Building Information Modeling (BIM) has been widely used in the past decade to enhance the design quality of Heating, Ventilation, and Air Conditioning (HVAC) systems. However, in specialized areas such as pharmaceutical facilities, HVAC design has traditionally relied on Computer-Aided Design (CAD) drawings. This conventional approach does not allow for the simulation of temperature distribution or the verification of system efficiency, which may lead to design failures. To address these challenges in pharmaceutical facilities, this study proposed a BIM-based approach for optimizing HVAC design with Computational Fluid Dynamics (CFD). By employing CFD to simulate the dynamic airflow conditions of pharmaceutical clean rooms, the effectiveness of HVAC systems can be verified. A case study of a clean room HVAC design is presented to demonstrate the workflow. The results of the case study indicated that the pharmaceutical temperature requirements were met within 1 °C during the design optimization simulation, and there was a 95% match in the 72 h temperature mapping test during site validation. The results confirmed that using CFD with BIM not only successfully simulates the design intentions of indoor air quality but also suggests HVAC system optimization for the required clean room design. The findings of this paper contribute to the body of knowledge on overcoming the limitations of the traditional CAD-based HVAC design process and provide valuable insights on optimizing HVAC design with BIM and CFD technologies.

Along with the increasing number of prefabricated buildings being constructed in China each year, the incident rate of hoisting operations has been continuously rising. In order to improve construction safety in hoisting operations of prefabricated buildings, this paper analyzes the construction workers’ unsafe behaviors using the Hazard and Operability (HAZOP) method. A questionnaire survey and a literature review were first performed to gather information on safety risks and influencing factors during each stage of hoisting operations, and the survey results were statistically analyzed using the SPSS software. Next, HAZOP was applied to identify the deviation and change of the unsafe behaviors as well as their causes, consequences, and countermeasures. Finally, a case study was presented to verify the effectiveness of the countermeasures through a comparison and evaluation method from experimental economics. This paper demonstrates the use of HAZOP to analyze construction workers’ unsafe behaviors in hoisting operations of prefabricated buildings, and effective countermeasures in each stage of hoisting operations are proposed to mitigate unsafe behaviors. This paper therefore provides an innovative method and a theoretical foundation for reducing unsafe behaviors in hoisting operations of prefabricated buildings and serves as a reference for decision-making for hoisting safety policies in prefabricated construction projects.

Small unmanned aerial systems (UAS) have been increasingly popular in surveying and mapping tasks. While photogrammetry has been the primary UAS sensing technology in other industries, construction activities can also benefit from accurate surveying measurements from airborne LIDAR. This paper discusses a custom-designed low-cost UAS-based LIDAR system that can effectively measure construction excavation and bulk piles. The system is designed with open interfaces that can be easily upgraded and expanded. An error model was developed to predict the horizontal and vertical errors of single point geo-registration for a generic UAS-LIDAR. This model was validated for the proposed UAS-LIDAR system using calibration targets and real-world measurements from different scenarios. The results indicated random errors from LIDAR at approximately 0.1 m and systematic errors at or below centimeter level. Additional pre-processing of the raw point cloud can further reduce the random errors in LIDAR measurements of bulk piles.

To continuously improve the efficiency of the construction project delivery process, various innovative methods and technologies have been developed and adopted in the past decades. Among these methods, modular construction has become a popular option due to its short on-site installation time generated by off-site prefabrication. However, the process of modular construction requires a highly integrated system to accurately connect multiple phases, including material packaging, transportation logistics, locating and tracking, and on-site installation. Accordingly, this process typically poses a significant challenge for contractors to efficiently manage the materials needed for daily tasks. This paper introduces a construction material management system that integrates every phase from off-site packaging to on-site installation. The integrated system was developed based on Logistic Chain and Building Information Modeling (BIM) using a three-layer framework, namely material packaging, inventory management, and material locating and tracking. The new system utilizes recent innovative technologies for transparent consolidation and highly efficient operation of off-site inventory management and on-site visualization. The developed system was further examined in a real-world case study project. The material handling time was then analyzed and compared with benchmark data without using the integrated system. The results indicated that the newly developed system was able to effectively reduce the time of locating materials and the rate of missing materials during on-site installation. In addition, this case study project added value to the verification of the broader system’s capabilities for inventorying, tracking, and visualizing construction materials. The findings of this project provide valuable knowledge and insight into improving construction efficiency through an integrated material management system. Future research is needed to expand the applicability of multiple framework designs and assess the cost–benefit analysis for production-scale and commercial use.