1 Department of Quantity Surveying, Federal Polytechnic Bida, Niger State Nigeria.
2 Department of Civil Engineering, University Of Cross River State Calabar, Cross River State Nigeria.
3 Department of AI laboratory, National Centre for Artificial Intelligence and Robotics FCT Abuja Nigeria.
4 Department of Architectural Technology Federal Polytechnic IIlaro.
5 Department of Civil Engineering, Ladoke Ankintola University of Technology Ogbomosho Oyo, Nigeria.
Review Article
World Journal of Advanced Research and Reviews, 2024, 24(02), 1833-1846
Received on 08 October 2024; revised on 16 November 2024; accepted on 19 November 2024
Building Information Modeling (BIM) has revolutionized the Architecture, Engineering, and Construction (AEC) industry, transforming how building lifecycle data is managed and visualized. By consolidating physical and functional characteristics into a shared digital model, BIM facilitates collaboration, minimizes rework, and streamlines planning and execution. In sustainability, BIM supports "Green BIM" practices that reduce carbon footprints by enabling energy modeling and lifecycle analysis. However, despite these advances, BIM faces interoperability issues, largely due to proprietary software formats, leading to isolated data silos that impede efficient data exchange across platforms. The integration of Artificial Intelligence (AI) into BIM introduces groundbreaking solutions to these challenges. AI enhances BIM through automation of design validation, clash detection, and real-time data analysis, transforming BIM into an adaptive system capable of proactive decision-making. AI applications, including predictive maintenance, generative design, and real-time construction monitoring, promise higher safety standards, reduced errors, and improved lifecycle management. However, AI-enhanced BIM adoption is hampered by technical, ethical, and financial challenges, such as data quality, privacy concerns, and high implementation costs. Addressing these obstacles with standardized data protocols, workforce upskilling, and collaborative frameworks can maximize the potential of AI-driven BIM, advancing sustainability, efficiency, and resilience within the construction industry.
Building Information Modeling (BIM); Artificial Intelligence (AI); Sustainability; Interoperability; Predictive Maintenance
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Christiana Ukamaka Aleke, Wofai Omini Usang, Abiamamela Obi-obuoha, Ahmed Abiodun Jolaosho and Olayemi Olayinka Michael. Artificial Intelligence as a tool for enhancing Building Information Modeling (BIM). World Journal of Advanced Research and Reviews, 2024, 24(2), 1833-1846. Article DOI: https://doi.org/10.30574/wjarr.2024.24.2.3517