Air Quality Monitoring Using MQ135 Gas Sensor and Arduino Uno

Abstract: This paper presents the design and implementation of an air quality monitoring system based on an MQ135 gas sensor and an Arduino Uno microcontroller. The MQ135 sensor detects common pollutants (e.g. CO₂, NH₃, benzene, smoke) by measuring changes in air conductivity, and its analogy output is processed by the Arduino board. Sensor readings are calibrated against known conditions, and then converted to parts-per-million (PPM) levels. The system displays real-time air quality readings on an LCD and can trigger alerts when thresholds are exceeded. Data collection and analysis are demonstrated through sample readings in different environments. The system’s accuracy, limitations, and potential improvements (such as IOT connectivity, mobile apps, and machine learning) are discussed. This project shows that a low-cost MQ135/Arduino platform can provide continuous air quality data for environmental monitoring.

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Publication Details

Journal
International Journal of Latest Technology in Engineering Management & Applied Science
Published
2025-06-28
DOI
https://doi.org/10.51583/ijltemas.2025.140500119
Citations
1
Primary Topic
IoT-based Smart Home Systems
Type
article
Field-Weighted Citation Impact
0.73
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Air Quality Monitoring Using MQ135 Gas Sensor and Arduino Uno

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Air Quality Monitoring Using MQ135 Gas Sensor and Arduino Uno

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article en
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Abstract

Abstract: This paper presents the design and implementation of an air quality monitoring system based on an MQ135 gas sensor and an Arduino Uno microcontroller. The MQ135 sensor detects common pollutants (e.g. CO₂, NH₃, benzene, smoke) by measuring changes in air conductivity, and its analogy output is processed by the Arduino board. Sensor readings are calibrated against known conditions, and then converted to parts-per-million (PPM) levels. The system displays real-time air quality readings on an LCD and can trigger alerts when thresholds are exceeded. Data collection and analysis are demonstrated through sample readings in different environments. The system’s accuracy, limitations, and potential improvements (such as IOT connectivity, mobile apps, and machine learning) are discussed. This project shows that a low-cost MQ135/Arduino platform can provide continuous air quality data for environmental monitoring.

International Journal of Latest Technology in Engineering Management & Applied ScienceVol. 14(5)
Tokyo Polytechnic University (JP)
Openalex Percentile: Top 27%
IoT-based Smart Home Systems
0.73
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