Application of Fuzzy Logic for Automatic Air Circulation Control System in Smoking Rooms Based on IoT - Mikhail Hibrizi; Ariel Pasha Ramaditya; Muhammad Dzaky Azzshahir (Batrisya Education, 2026)
Indoor air quality (IAQ) in smoking rooms presents significant health risks due to the accumulation of pollutants such as carbon monoxide (CO) and cigarette smoke. Conventional ventilation systems typically operate using constant speed or threshold-based ON/OFF control, which cannot provide adaptive responses to dynamic pollutant variations. This study proposes an Internet of Things (IoT)–based automatic air circulation control system utilizing a Mamdani Fuzzy Inference System (FIS) to regulate exhaust fan speed proportionally in real time. The system integrates MQ-2 and MQ-7 sensors with an ESP32 microcontroller for pollutant detection and processing. The fuzzy control mechanism consists of fuzzification, MIN implication, MAX aggregation, and Centroid of Area (CoA) defuzzification to generate a crisp output representing fan speed. The output is converted into an 8-bit PWM signal for proportional actuator control, while environmental data are transmitted via MQTT for real-time monitoring. Experimental and simulation results demonstrate that the proposed fuzzy-based controller provides smoother and more adaptive ventilation performance compared to conventional ON/OFF control, particularly under moderate pollution conditions. The closed-loop architecture improves responsiveness and operational efficiency for intelligent smoking room ventilation management.