The article presents a state-of-the-art analysis of Generative AI’s role in the construction industry. It identifies productivity challenges in design, planning, procurement, inspection, and maintenance processes. Generative AI, which can create novel and realistic data based on input or prior knowledge, offers innovative solutions to these challenges. The study reviews and categorizes existing and emerging generative AI opportunities and challenges in construction. It proposes a framework for construction firms to build customized generative AI solutions using their data. The framework involves data collection, dataset curation, training custom large language model (LLM), model evaluation, and deployment. A case study shows that retrieval augmented generation (RAG) improves the baseline LLM in terms of quality, relevance, and reproducibility. The study provides a comprehensive analysis and practical framework to guide the adoption of generative AI techniques to enhance productivity, quality, safety, and sustainability across the construction industry.
Publication date: 16 Feb 2024
Project Page: Not provided
Paper: https://arxiv.org/pdf/2402.09939
