An Intelligent Fuzzy Logic-Based Framework for Optimizing Energy Consumption in Residential Buildings

Optimizing energy consumption and preventing its waste is one of the most pressing challenges of the modern era, particularly in the building sector, which is a dominant energy consumer globally. In Iran, residential buildings account for the largest share of the country's total energy consumption, highlighting a critical need for innovative management solutions. This research proposes and develops an integrated, automated system for managing lighting and heating in residential buildings using fuzzy logic control. The system is designed to optimize energy use dynamically without compromising occupant visual and thermal comfort. Developed and simulated within the MATLAB R2021b environment, the framework consists of two dedicated subsystems. The lighting subsystem processes eight socio-environmental input parameters—age, education, occupation, economic status, lifestyle, marital status, geographical conditions, and activity level—through a refined set of 629 fuzzy rules to determine optimal illumination levels. Simultaneously, the heating subsystem utilizes six inputs—age, climate condition, activity level, lifestyle, Body Mass Index (BMI), and gender—governed by 74 fuzzy rules to ascertain the preferred thermal setting. Complementing this, the study includes a climatic analysis of solar radiation potential in Shiraz, Iran, utilizing RELUX software for precise daylighting calculations. This analysis confirms the region's high capacity for leveraging solar energy to significantly reduce dependence on artificial lighting and mechanical heating. The results conclusively demonstrate that the proposed fuzzy logic systems can effectively and intelligently manage energy consumption by seamlessly adapting to both user-specific conditions and variable environmental factors, offering a robust model for sustainable building management.