Identifying and assessing the internet of things implementation barriers for sustainable building projects: SEM-ANN approach

The Internet of Things (IoT) adoption in building projects has evolved into a standard practice based on established principles over the past two decades. Integrating IoT can support achieving social, economic, and environmental aspects. Despite technological advancements, the construction sector has been slow to embrace digital transformation due to its reliance on conventional, experience-based decision-making, manual processes, and fragmented project management methods that lack standardization. These informal approaches hinder the integration of technology by limiting data availability, reducing interoperability between stakeholders, and creating resistance to change. Hence, this research aims to develop a framework for integrating IoT technologies efficiently into construction projects by analyzing the barriers to IoT implementation. To accomplish this objective, a survey was administered to specialists in the construction field to assess the importance of barriers to IoT adoption. Then, the barriers were ranked using exploratory factor analysis. A deep artificial neural network was employed to supplement the partial least squares-structural equation modeling results and improve forecasting accuracy. The results can aid decision-makers in the building industry as they strive to adopt IoT to reduce expenses and enhance productivity.