Towards 4D BIM: A Systematic Literature Review on Challenges, Strategies and Tools in Leveraging AI with BIM

In moving toward the fourth dimension of building information modeling (4D BIM), this study systematically reviews the literature on challenges, strategies, and tools in 4D BIM-related research. To address the limitation of the static nature of knowledge represented in traditional building information modeling (BIM), 4D BIM incorporates the time dimension into BIM systems to anticipate potential delays, optimize workflows, and improve overall project efficiency in the architecture, engineering, and construction (AEC) industry. Although existing BIM research has covered various aspects, in-depth review studies specifically on 4D BIM remain scarce. Following a systematic search and data analysis, this work examines research contexts (building information models, lean systems, ontology frameworks, predictive strategies, and tools, software and techniques) in 4D BIM research and evaluates them qualitatively. The research and evaluation identified several key strategies for advancing 4D BIM, including the integration of lean methodologies, predictive strategies, and ontology frameworks. These approaches contribute to the automation of information sharing and the optimization of processes within AEC digital infrastructures. This review highlights the gaps in current research and emphasizes the importance of integrated digital solutions while also classifying the existing tools, software, and standards related to 4D BIM while presenting a foundation for future research on AI-driven solutions.