Machine Learning for Improving Construction Productivity: A Systematic Literature Review

Abstract

Machine learning, as one of the Artificial Intelligence (AI) approaches, has been widely adopted in various fields and is now becoming one of the emerging technologies revolutionizing the construction industry. One of the machine learning applications in the construction industry is to improve construction productivity. However, the current application in this field primarily focuses on enhancing productivity within specific, isolated construction tasks, often lacking real-world applicability. Therefore, a more holistic framework aimed at enhancing productivity across the entire construction process is desired by industry professionals. To enhance readiness for constructing such a framework, a methodical examination of existing literature has been carried out to explore the status of utilizing machine learning to enhance efficiency in construction practices. This review not only identifies but also categorizes the existing machine-learning applications and practices. Additionally, it highlights limitations and potential enhancements within current machine learning techniques, offering valuable insights for future research endeavors.