<![CDATA[This study presents a simulation-based analysis of an automatic exhaust fan control system using the Mamdani Fuzzy Inference System (FIS) integrated within an Internet of Things (IoT) framework. Poor indoor air quality, along with uncontrolled temperature and humidity levels in enclosed environments, significantly affects human comfort and equipment reliability. The proposed system utilizes temperature and humidity data as input variables, which are processed through a Mamdani FIS to generate proportional control signals for exhaust fan speed regulation. Triangular and trapezoidal membership functions were designed to model environmental conditions, while the Center of Area (COA) method was applied for defuzzification to ensure smooth output transitions. The system was evaluated using MATLAB Fuzzy Logic Toolbox, and the surface analysis demonstrates stable and continuous control behavior across varying environmental conditions. The results indicate that the Mamdani fuzzy approach provides smooth, adaptive, and energy-efficient control compared to conventional threshold-based systems. Furthermore, the integration of IoT enables real-time monitoring and enhances operational flexibility. These findings confirm that Mamdani FIS is a suitable method for intelligent exhaust fan automation. ]]>
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