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IOT based Vehicle Emission Monitoring and Prediction System

Author

Listed:
  • Naru Sivakumar
  • Savu Sai Mounika
  • Rayala Sai Poojitha
  • Mamidi Kusuma Kumari
  • Sambangi Siddardha
  • Saketi Jairam

Abstract

The IoT-Based Vehicle Emission Monitoring and Prediction System is designed to continuously monitor vehicular exhaust emissions and predict pollution levels to enhance environmental safety and regulatory compliance. The system integrates multiple sensors with an Arduino microcontroller to measure carbon monoxide (CO) using the MQ7 sensor, carbon dioxide (CO₂) levels, overall air quality via the MQ135 sensor, and ambient temperature and humidity through the DHT11 sensor. Real-time readings are displayed locally on an LCD for immediate awareness. Using a NodeMCU, the collected data is transmitted to the cloud for remote monitoring and visualization through platforms like ThingSpeak. A Python-based Random Forest machine learning model analyzes both historical and real-time data to predict future emission trends and detect abnormal pollution levels. If emission levels exceed safe limits, a buzzer triggers an alert. The system is powered by a regulated 12V adapter and integrated using connectors, offering a robust, intelligent, and automated approach for vehicle emission monitoring, prediction, and environmental protection.

Suggested Citation

  • Naru Sivakumar & Savu Sai Mounika & Rayala Sai Poojitha & Mamidi Kusuma Kumari & Sambangi Siddardha & Saketi Jairam, 2026. "IOT based Vehicle Emission Monitoring and Prediction System," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 12(2), pages 220-229, April.
    • Handle: RePEc:jbh:ijsrcs:v12:y2026:i2:id:1919
    DOI: 10.32628/CSEIT2612212
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT2612212
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