Integration of Artificial Intelligence and Smart Technologies in Offsite Construction: A Comprehensive Review

Abstract

Due to the ongoing rapid pace of advancement in information technology, the integration of Artificial Intelligence (AI) and Smart Technologies (ST) in offsite construction is transforming the industry by enhancing efficiency, innovation, and safety. This comprehensive review examines the application of AI and ST subfields, including Machine Learning (ML) algorithms such as k-Nearest Neighbors (k-NN), logistic regression, linear regression, Support Vector Machines (SVM), and neural networks, as well as Deep Learning (DL) algorithms like Feedforward Neural Networks (FNN), Convolutional Neural Networks (CNN), Generative Adversarial Networks (GAN), Variational Autoencoders (VAE), and Recurrent Neural Networks (RNN), in offsite construction. Utilizing secondary data, descriptive survey methods, systematic review, and content analysis, the study maps the current state of AI and ST applications such as Building Information Modeling (BIM) and other technologies such as the Internet of Things (IoT), Augmented Reality (AR), digital twins and identifies trends, opportunities, and challenges. This review also discusses the need for research investment and the development of regulatory frameworks to foster innovation and sustainable growth. Ethical considerations, including data quality, transparency, privacy, employment impacts, and governance, are also critical to the responsible adoption of these technologies. This research concludes with a call for strategic research and development to bridge existing gaps and fully leverage AI and ST for industry-wide benefits. Grounded based on the Unified Theory of Acceptance and Use of Technology (UTAUT), the review provides valuable information to academics, practitioners, and policymakers aiming to harness the benefits of AI and ST in offsite construction.