Implementation of Fuzzy Logic on Motorcycle Emission Testing Device Using Multi-Gas Sensors - Afridon, M.; Syah, Khairudin; Marzuarman; Susanto, Heri; Arifin, Muhammad; Syindau Abdillah, M. Andrian; Ramadhan, M. Zaki Nawaf (INOVTEK Polbeng - Seri Informatika, 2025)
Manual motorcycle emission inspection often leads to inconsistent interpretation due to operator dependency. This study developed a motorcycle emission testing system using multi-gas sensors, consisting of ZE07-CO for CO, an infrared CO₂ sensor for CO₂, TGS2602 for VOC, and O₂ I2C DFRobot for oxygen concentration, integrated with an ESP32 microcontroller. Sensor data are transmitted in real-time via Bluetooth to a computer for processing and visualization on a graphical user interface. The measurement ranges were adjusted to match actual exhaust gas characteristics: CO 0–5000 ppm, CO₂ 0–50000 ppm, VOC 0–500 ppm, and O₂ 0–5%. Emission level classification was performed using the Mamdani fuzzy logic method with three triangular membership functions for each parameter and three output categories: low, medium, and dangerous. Tests on nine motorcycles showed four units classified as low emission (CO <1000 ppm; O₂ >2.4%), three as medium (CO 1100–2500 ppm; O₂ 1.5–2.0%), and two older vehicles classified as dangerous (CO >3500 ppm; VOC >350 ppm; O₂ <1%). The system successfully provides automatic and real-time emission assessment, although verification against standard emission testers and environmental compensation is required for broader practical implementation.