Digital Life Cycle Assessment Of Structural Systems Using BIM And Artificial Intelligence

Authors

  • Lusaka Sahu Research Scholar, Department of Civil Engineering, MATS University, Raipur Author
  • Shrishti Verma, Ms. Sakshi Sahu Assistant Professor, Department of Civil Engineering, MATS University, Raipur Author

Keywords:

Life Cycle Assessment, Building Information Modeling, Artificial Intelligence, Structural Materials, Environmental Impact.

Abstract

Life Cycle Assessment (LCA) has emerged as a critical methodology in evaluating the environmental impact of
structural materials and systems. With the rise of Building Information Modeling (BIM) and Artificial Intelligence
(AI)-based tools, computational LCA has been significantly enhanced in terms of accuracy, efficiency, and
integration. This paper reviews past work in the domain of computational LCA applied to structural materials
and systems, emphasizing the synergy of BIM and AI technologies. Through a comprehensive meta-analysis of
key studies from the past decade, we explore how digital innovations have shaped LCA methodologies. Findings
reveal that while integration efforts have advanced, standardization and data interoperability remain key
challenges. AI-driven analytics and machine learning models have shown promise in predictive modeling, while
BIM has facilitated data-rich environments for LCA execution. The study concludes with discussions on future
trends, limitations of existing approaches, and potential for broader application in sustainable construction

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Published

2025-05-22

Issue

Section

Articles

How to Cite

Digital Life Cycle Assessment Of Structural Systems Using BIM And Artificial Intelligence. (2025). INTERNATIONAL JOURNAL OF MANAGEMENT RESEARCH AND REVIEW, 15(2), 163-168. https://ijmrr.com/index.php/ijmrr/article/view/125