Off-site construction has been increasingly employed due to its advantages, for instance, improved quality control, reduced skills labour, faster construction time, decreased material wastage and safe working environment. As the most cutting-edge off-site construction, modular buildings have been utilised for residential building, student accommodation, and hotel projects. However, because of existing and underlying constraints, the adoption of modular buildings is still relatively low. To reveal factors hindering the development of high-rise modular buildings, a comprehensive literature review, coupled with a focus group study, were conducted. A questionnaire survey inquiring about all stakeholders was implemented to quantify constraints. The results were further examined according to a real-life case study. This paper manifested that “Lack of coordination and communication among stakeholders”, “Higher cost”, “Lack of government support”, “Lack of experience and expertise”, “Lack of building codes and standards”, “Poor supply chain integration”, and “Complexity of connection” are the top barriers curbing the uptake of modular buildings. The findings should provide a valuable reference for stakeholders adopting modular buildings, whilst mitigating risks amid modular construction. Future research is expected to exploit building information modelling and design for manufacture and assembly to alleviate these existing constraints and promote the performance of modular construction as well.

Scaffolding serves as one construction trade with high importance. However, scaffolding suffers from low productivity and high cost in Australia. Activity Analysis is a continuous procedure of assessing and improving the amount of time that craft workers spend on one single construction trade, which is a functional method for monitoring onsite operation and analyzing conditions causing delays or productivity decline. Workface assessment is an initial step for activity analysis to manually record the time that workers spend on each activity category. This paper proposes a method of automatic scaffolding workface assessment using a 2D video camera to capture scaffolding activities and the model of key joints and skeleton extraction, as well as machine learning classifiers, were used for activity classification. Additionally, a case study was conducted and showed that the proposed method is a feasible and practical way for automatic scaffolding workface assessment.