Construction workers' cognitive statuses affecting their safety and productivity are essential for successful construction management. Electroencephalogram (EEG) provides a potential objective tool for measuring and computing the cognitive status of construction workers. This study aims to answer how to adopt EEG for measuring and computing construction workers' cognitive statuses through a critical review. The literature search and selection process included 21 eligible articles. The content analysis was then conducted from three aspects of investigated cognitive statuses, experiment design, and data analysis. The investigated cognitive statuses include vigilance, mental fatigue, mental stress, attention, mental workload, and emotional state. The experiment design is reviewed from the perspective of participant selection, device selection and electrode deployment, task design, and label selection. The data analysis involves EEG signal preprocessing, feature extraction, and cognitive status computation. Five major limitations of the existing studies have been identified, and five future research directions are proposed to address these limitations. This review provides guidance for researchers to use EEG for measuring and computing various cognitive statuses of construction workers. It also provides valuable suggestions for future research and on-site construction management.

Exiting green building assessment standards sometimes cannot work well for large-scale public buildings due to insufficient attention to the operation and maintenance stage. This paper combines the theory of life cycle assessment (LCA) and building information modeling (BIM) technology, thereby proposing a green building assessment method by calculating the greenhouse gas emissions (GGE) of buildings from cradle to grave. Life cycle GGE (LCGGE) can be divided into three parts, including the materialization stage, the operation and maintenance stage, and the demolition stage. Two pieces of BIM software (Revit and Designbuilder) are applied in this study. A museum in Guangdong, China, with a hot summer and warm winter is selected for a case study. The results show that BIM can provide a rich source of needed engineering information for LCA. In addition, the operation and maintenance stage plays the most important role in the GGE reduction of a building throughout the whole life cycle. This research contributes to the knowledge body concerning green buildings and sustainable construction. It helps to achieve the reduction of GGE over the whole life cycle of a building. This is pertinent to contractors, homebuyers, and governments who are constantly seeking ways to achieve a low-carbon economy.

Life cycle cost analysis (LCCA) plays an essential role in the economic sustainability assessment of buildings, and building information modeling (BIM) offers a potentially valuable approach to fulfilling its requirement. However, the state of LCCA based on BIM is unclear despite previously published works. Therefore, this paper aims to address this gap by reviewing 45 relevant peer-reviewed articles through a systematic literature search, selection, and assessment. The results show that three data exchange methods integrate BIM and LCCA through data input, calculation, and output. Precision management, optimization measures, and parameter analysis through BIM significantly improve the value of buildings. Also, a methodological framework is summarized that combines LCC with other indicators based on BIM to consider economic, environmental, and social impacts, which can be monetized to assess life cycle sustainability costs. These findings provide insights for scholars and practitioners.