ECAM: a BIM–AR integrated framework for optimized energy and cost performance in material selection
Omid Alijani Mamaghani et al.
What the paper says
Purpose This study addresses the critical need for energy efficiency in construction by developing and validating an intelligent, integrated framework to support informed material selection during the early design phase. The primary objective is to integrate Building Information Modeling (BIM), Augmented Reality (AR), and automated energy analysis to identify and recommend materials that minimize operational energy costs, tailored to a project’s specific location. Design/methodology/approach The methodology establishes a cohesive digital workflow. A BIM model is created in Autodesk Revit and analyzed using Autodesk Insight Carbon Analysis for energy performance. A custom C# plugin, the Energy and Cost Analysis of Materials (ECAM), automates the processing and ranking of energy data. The results are then visualized in an immersive AR environment developed in Unity 3D, enabling interactive, on-site decision-making. Findings The ECAM framework successfully translates complex energy simulation data into a clear, ranked list of material options. In a case study of a residential building in Chabahar, Iran, wood emerged as the most energy-efficient façade material, offering a potential annual operational energy cost saving of 9.5% compared to ceramic. The AR interface proved to be an effective medium for designers and stakeholders to visualize material trade-offs in context, enhancing decision quality and communication. Originality/value This research presents a novel framework bridging abstract energy analysis and practical design application. Its originality lies in combining BIM, a custom automation plugin (ECAM), and an immersive AR interface into a single workflow. The framework provides designers and clients with a practical, data-driven tool to optimize material selection, reduce long-term operational costs, and advance sustainable building practices.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.