Optimizing smart window glass selection to address contemporary environmental challenges using fuzzy multi-criteria decision analytics

In recent times, the world has been dealing with multiple environmental crises, including rising global temperatures, excessive energy consumption, elevated urban temperatures, and increasing carbon emissions from the building industry. As buildings have a significant impact on energy use, it is essential to address these challenges. In particular, window glass plays a significant role in controlling heat transfer, regulating indoor temperatures and reducing the dependence on artificial cooling. Therefore, selecting the most suitable energy-efficient glass has become crucial for sustainable development. Construction technology has introduced specialized glass materials for windows, including smart window technologies that automatically regulate heat and light. This study aims to identify the most suitable energy-efficient glass using a fuzzy multi-criteria decision-making method. Here, eight different alternatives are evaluated against eleven conflicting criteria classified as performance enhancing criteria (PEC) and performance reducing criteria (PRC). The Simultaneous Evaluation of Criteria and Alternative (SECA) method is employed for determining criteria weights, and the COmbinative Distance-based ASsessment (CODAS) approach is utilized to evaluate ranks of the alternatives. To ensure reliability and robustness, the study performed comparative and sensitivity analyses. The results indicate that electrochromic (EC) windows (A4) are the most suitable smart glazing technology among the considered alternatives. The results help urban planners and architects select energy-efficient glass for smart windows.