IoT-based Exhaust Gas Emission Detection System for Motorized Vehicle

The increase in the number of motorized vehicles results in air pollution by emission gases such as carbon dioxide (CO2), carbon monoxide (CO), and hydrocarbons (HC). This causes air quality to decline and threatens public health. This research aims to monitor vehicle emissions using ESP32. MQ-7, MQ-2, and MQ-135 sensors are used to detect exhaust emissions. Detected gas data is sent to the Blynk platform for real-time monitoring, printed using a thermal printer, and stored in Firebase for further analysis. The MQ-7 sensor detects CO, the MQ-2 detects HC, and the MQ-135 detects CO2. The research results show that the tool developed is successful in monitoring and analyzing vehicle exhaust emissions. This hardware is capable of detecting emissions precisely, supported by the Blynk application for real-time monitoring and Realtime Database for data storage. Variations in fuel type, such as 90 octane and 92 octane, significantly influence CO2 emission levels. On an EFI engine, CO2 emissions range from 0.9% to 2.2% for 90 octane, while on a carburetor engine the range is 1.33% to 2.87%. RPM variations also affect CO2 emissions, with a 92 octane EFI engine showing a range from 1.0% at low RPM to 2.63% at high RPM. Overall, EFI engines show better performance with lower CO emissions compared to carburetor engines.

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Publication Details

Journal
International Journal of Frontier Technology and Engineering
Published
2024-12-30
DOI
https://doi.org/10.33795/ijfte.v3i1.5675
Primary Topic
Vehicle emissions and performance
Type
article
Field-Weighted Citation Impact
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article

IoT-based Exhaust Gas Emission Detection System for Motorized Vehicle

Zakiyah Amalia, Sukron Kadir
International Journal of Frontier Technology and Engineering
Vehicle emissions and performance
article

IoT-based Exhaust Gas Emission Detection System for Motorized Vehicle

Zakiyah Amalia, Sukron Kadir
article en

Abstract

The increase in the number of motorized vehicles results in air pollution by emission gases such as carbon dioxide (CO2), carbon monoxide (CO), and hydrocarbons (HC). This causes air quality to decline and threatens public health. This research aims to monitor vehicle emissions using ESP32. MQ-7, MQ-2, and MQ-135 sensors are used to detect exhaust emissions. Detected gas data is sent to the Blynk platform for real-time monitoring, printed using a thermal printer, and stored in Firebase for further analysis. The MQ-7 sensor detects CO, the MQ-2 detects HC, and the MQ-135 detects CO2. The research results show that the tool developed is successful in monitoring and analyzing vehicle exhaust emissions. This hardware is capable of detecting emissions precisely, supported by the Blynk application for real-time monitoring and Realtime Database for data storage. Variations in fuel type, such as 90 octane and 92 octane, significantly influence CO2 emission levels. On an EFI engine, CO2 emissions range from 0.9% to 2.2% for 90 octane, while on a carburetor engine the range is 1.33% to 2.87%. RPM variations also affect CO2 emissions, with a 92 octane EFI engine showing a range from 1.0% at low RPM to 2.63% at high RPM. Overall, EFI engines show better performance with lower CO emissions compared to carburetor engines.

International Journal of Frontier Technology and EngineeringVol. 3(1)
State University of Malang (ID)
Openalex Percentile: Top 72%
Vehicle emissions and performance
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IoT-based Exhaust Gas Emission Detection System for Motorized Vehicle — Zakiyah Amalia, Sukron Kadir · International Journal of Frontier Technology and Engineering (2024) | TGRS Research Map | TGRS