Maintaining thermal comfort during sleep while minimizing energy consumption has become increasingly important under rising summer temperatures. This study presents the design and implementation of an intelligent fuzzy-logic–based control system for the adaptive regulation of household electric fans in sleep environments. The proposed system integrates an infrared array sensor to simultaneously detect body and room temperatures, with a Mamdani-type fuzzy inference controller implemented via MATLAB–Arduino communication. The controller dynamically adjusts the fan speed according to nine linguistic rules derived from thermal comfort criteria. Experimental validation was conducted across multiple temperature scenarios ranging from 25 °C to 45 °C, with body temperatures varying between 36 °C and 39 °C. Results show stable adaptive behavior, with fan speed smoothly varying between 12% and 82% according to thermal conditions. The proposed approach offers greater flexibility than fixed-speed operation and model-based controllers, providing an energy-efficient, personalized solution for smart home thermal management.
Al-Areqi et al. (Tue,) studied this question.
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