Evaluation of Climate and Energy Compatibility in Smart Cities through Fuzzy Logic Approach

Abstract

Building-based energy efficiency levels in five cities located in different climate zones of Turkey (Erzurum, Antalya, Rize, Istanbul, and Gaziantep) were analyzed using the fuzzy logic method. For each city, multi-criteria variables such as thermal insulation quality, annual energy consumption, building age, and user energy awareness were evaluated, and corresponding energy efficiency scores were calculated. According to the results, Istanbul demonstrated high energy efficiency, Antalya and Rize showed moderate efficiency, while Erzurum and Gaziantep exhibited low efficiency. The findings indicate that, in addition to climatic conditions influencing energy demand, factors such as building age and user behavior are also significant determinants. Within the context of the smart city approach, this analysis highlights the importance of data-driven decision support systems in urban energy management strategies. Uncertainty-based systems like fuzzy logic offer a flexible means of evaluating complex relationships between multiple variables in smart cities. Moreover, the identification of regions with low efficiency paves the way for the development of policies such as urban transformation, public awareness campaigns, and the integration of innovative technologies. In this regard, climate-specific energy solutions tailored to each city play a critical role in achieving the sustainability goals of smart city planning. This study emphasizes the necessity of considering regional differences in energy efficiency in the implementation of smart city applications.