2571-1075ISSN (Online)
Volume 12 , Issue 1 , PP: 58-74, 2026 | Cite this article as | XML | Html | PDF | Full Length Article
Batoul Hasanin 1 * , Karel Pavelka 2
Doi: https://doi.org/10.54216/IJBES.120104
Post-conflict reconstruction often prioritizes speed and cost over long-term sustainability, leading to environmental, social, and economic inefficiencies. This study proposes an integrated framework that combines Building Information Modeling (BIM) and Artificial Intelligence (AI) to enhance multi-dimensional sustainability in reconstruction projects. An exploratory explanatory case study methodology was adopted, analyzing two Syrian case studies—a service building in Tartous and the Al-Qarabis neighborhood in Homs—through BIM-based simulations and AI-driven optimization. BIM served as the core data platform, while AI facilitated scenario analysis and optimization across both design and operational stages. Sustainability indicators were explicitly mapped to relevant Sustainable Development Goals (SDGs 7, 9, 11, 12, and 13). Results indicate that BIM–AI integration significantly improves energy efficiency, operational performance, spatial adequacy, and life-cycle cost effectiveness, effectively translating sustainability from a conceptual goal into measurable outcomes. The framework provides empirical evidence for operationalizing Building Back Better principles and offers a transferable methodology applicable to other post-conflict reconstruction contexts. Future studies could explore the incorporation of additional AI-driven decision support tools or expand the framework to diverse post-conflict regions to further validate its applicability and impact.
Building Information Modeling (BIM) , Artificial Intelligence (AI) , Post-Conflict Reconstruction , Multi-Dimensional Sustainability , Sustainable Development Goals (SDGs) , Decision-Support Systems , Syria
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