• Dr. S. Elangovan
• Avalakunta Tharun
• Bellum Kushyanth Reddy
• Chittooru Mallikarjuna Dinesh
• Maram Saraschandra Reddy

In urban environments, idle vehicles can accumulate hazardous gases like CNG, CO, and CO₂, posing fire hazards and health risks. This project presents an IoT-based Air Quality Monitoring System using Machine Learning to assess in-vehicle air safety. A Random Forest model, trained on diverse gas concentration datasets, predicts air quality as normal or hazardous. The system integrates gas sensors (MQ-4, MQ-7, MQ-135) and a microcontroller for real-time data collection. Results are displayed via an LCD interface, ensuring timely alerts. This approach enhances vehicle safety by preventing gas-related incidents.

Air Quality Monitoring, IoT, Machine Learning, Random Forest, Vehicle Safety, Gas Sensors, CNG Detection, CO Monitoring, CO₂ Levels

"AIR QUALITY MONITORING SYSTEM IN A CAR USING ML AND IOT ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.d763-d768, March-2025, Available :http://www.jetir.org/papers/JETIR2503384.pdf

"AIR QUALITY MONITORING SYSTEM IN A CAR USING ML AND IOT ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppd763-d768, March-2025, Available at : http://www.jetir.org/papers/JETIR2503384.pdf