Rancang Bangun Sistem Pendeteksi Dan Kontrol Kadar Asap Rokok Menggunakan Metode Fuzzy Logic

Abstract

Exposure to cigarette smoke in enclosed spaces has the potential to cause serious health impacts, especially for passive smokers. This study designs a cigarette smoke detection and control system based on Tsukamoto Fuzzy Logic by employing the MQ-7 sensor to detect carbon monoxide (CO) and the DHT22 sensor to measure room temperature. The acquired data are processed through the stages of fuzzification, rule inference, and defuzzification. The output in the form of a PWM signal is used to control the speed of a DC fan as an air circulation actuator, while a buzzer functions as a warning alarm. The test results show that the system is capable of operating in real time and adapting to environmental conditions. When the temperature is 30.5 °C and the smoke concentration reaches 491 PPM, the fan rotates at maximum speed with a PWM value of 220 and the buzzer is activated. Conversely, at a temperature of 24.0 °C and a smoke concentration of 173 PPM, the fan rotates at medium speed with a PWM value of 113 and the buzzer remains inactive. A comparison between measured and calculated fan speed values yields an average difference of 3.627 PWM and an error of 2.666%, indicating the system’s performance in controlling fan speed according to room conditions. This design can be applied to smoke control systems in enclosed spaces and supports the implementation of smoke-free areas.