Exhaust Gas Emission Monitoring System for Motor Vehicles Based on Sensors and the KNN (K-Nearest Neighbor)
Sistem Pemantauan Emisi Gas Buang Kendaraan Bermotor Berbasis Sensor dan KNN (K-Nearest Neighbor)
DOI:
https://doi.org/10.21070/ups.10531Keywords:
Air Pollution Monitoring, Emission Classification, Gas Sensors, K-Nearest Neighbor, Vehicle Exhaust EmissionsAbstract
The increasing number of motor vehicles has contributed to higher exhaust emissions, leading to a decline in air quality. This study aims to design a sensor-based monitoring and classification system for vehicle exhaust emissions with simple implementation and low cost. The system uses a microcontroller to measure emission parameters including carbon monoxide (CO), carbon dioxide (CO₂), hydrocarbons (HC), and oxygen (O₂). Sensor data are processed using the K-Nearest Neighbor method with Euclidean distance calculations to classify emission levels. The classification results are then compared with measurements from a manufacturer’s emission testing device used as a reference. Experimental results show that the proposed system is able to classify vehicle emission levels with an accuracy of 75%. Although slight differences occur due to sensor characteristics, the classification results remain consistent with the reference device and can support real-time emission monitoring.
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