Machine Learning and Artificial Intelligence Applications in Building Construction: Present Status and Future Trends

The use of Machine Learning (ML), Deep Learning, and Artificial Intelligence (AI) in building construction has been gaining traction since the mid 2000s. The ability to process the ever-increasing construction data, identify patterns, and predict future values has encouraged researchers to develop informed decision-making applications. This provides solutions to the challenges faced in the different areas of construction. This paper provides a literature review to identify, review, and categorize the existing body of knowledge involving the research and implementation of AI and ML in building construction. Related papers from journals were searched and identified using Scopus and Web of Science databases. Domain areas reviewed included clash detection, construction contract, cost, documents, equipment, labor, material, monitoring, planning, and scheduling productivity, risk, safety, and waste. Research studies reviewed are summarized and analyzed to identify gaps, describe the utilized algorithms and their applications, and aid in subsequent work by the research team.