Real-time outdoor air quality monitoring system

• Main Authors: Abiduzzaman, S M, Mansor, Hasmah, Gunawan, Teddy Surya, Ahmad, Robiah
• Format: Conference or Workshop Item
• Language: English; English
• Published: IEEE 2021
• Subjects: TK7885 Computer engineering
• Online Access: http://irep.iium.edu.my/92229/1/92229_Real-Time%20Outdoor%20Air%20Quality%20Monitoring%20System.pdf; http://irep.iium.edu.my/92229/7/92229_Real-Time%20Outdoor%20Air%20Quality%20Monitoring%20System_Scopus.pdf; http://irep.iium.edu.my/92229/; https://ieeexplore.ieee.org/abstract/document/9526332?casa_token=MrdSD2QhlGcAAAAA:y0Kp2Er_RTyevoUE2jb8VXQHgYagjSxPImeq4lxcrebyFBrX_wBZAGZmW1uQAle9gNz7K2UZ-A; https://doi.org/10.1109/ICSIMA50015.2021.9526332

Air pollution has harmed human health as a human cannot live without breathing. Even more worrying is that air pollution seems to be increasing day by day due to man-made pollution or natural pollution like a massive forest fire. Due to no real-time monitoring device being implemented, the authorities are unaware of the real-time conditions of air quality. Therefore, this project is aimed to give real-time air quality and location data by designing and developing a portable device and mobile app capable of producing and broadcasting real-time Air Pollutant Index (API) and GPS coordinates. In this work, various air pollutant gases and problems of the present air quality monitoring system have been reviewed. Two different pollutant gas sensors, i.e., Carbon Monoxide (CO) and Nitrogen Dioxide (NO2) sensors, and NEO-6M Global Positioning System (GPS) module, have been proposed. Air Pollutant Index (API) value and location data are determined by the system and uploaded to the cloud database. The developed mobile app retrieves the data, and anyone with the mobile app can get information about the location and its air quality in real-time. The system has been tested at two different places, and the results were compared with existing air-quality websites that were available online. Results showed that the system provides a 92.3% accuracy that is 5.1% more accurate than other systems. The proposed system could provide an important building block for smart city development.