Publication: Internet of things based air quality monitoring system with audio feedback system
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Date
2020-08-01
Authors
Peh, Yong Ching
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Abstract
Due to the annual haze in Southeast Asia countries and a serious wildfire burning in Australia in 2020, the air quality has worsen around the world. It is causing global warming and climate change by inducing greenhouse effect. Besides, these air pollutants bring detrimental effects to human health such as cardiovascular disease and lung damage. Therefore, an air quality monitoring system that measures the concentration of air pollutants, temperature and humidity with audio feedback alerting system will be developed. A website for real-time measurements of air pollutants concentration, temperature and humidity will also be complemented together so that people can have access to these data any time anywhere. Moreover, the effects of location and time period on concentration of gases, temperature and humidity will be studied to know more about outdoor and indoor air pollution. This is due to the fact that people spend 90% of their time indoor although outdoor air pollution is far worse than indoor air pollution. The proposed system will constantly acquire air pollutant concentration, temperature and humidity. If the air pollutant concentration exceeds the dangerous threshold level, the LED will blink to give visual warning and the speaker will give audio warning with dangerous gases concentration level. Besides, if the user would like to know the air pollutant concentration without checking on the website, the user could wave its hand over the motion sensor so that the system will anounce the air pollutant concentration in audio form using speaker. First, MQ2 sensor will be used to measure carbon monoxide (CO), liquefied petroleum gas (LPG), smoke, methane (CH4) and propane (C3H8) while DHT22 sensor will be used to measure temperature and humidity. Next, Python algorithm will be developed to run the system. After finish developing the algorithm, a preliminary experiment will be conducted to test MQ2 and DHT22 before they are ready for data collection on outdoor environment under different conditions. Next, Firebase will be used as the database to store the data from MQ2 and DHT22. These data will be send to a website that was developed by the coding of CSS, HTML and JavaScript. From the data collection result of this research, the prototype system works well and can be used
in both indoor and outdoor condition. The highest average CO concentration that was obtained among the data collection locations was at USM guardhouse during afternoon
and it was merely 5.77 X 10-2 ppm, which was equivalent to an excellent air quality index (AQI) of 0.7. In conclusion, the proposed air quality monitoring system with audio
feedback feature with IoT technology is successfully developed and the air quality monitoring website is available for everyone who has a smartphone.