Ambient Air Monitoring System with Adaptive Performance Stability

• Published in: IEEE access 2022, Vol.10, p.1-1
• Main Authors: Purbakawaca, R., Yuwono, A.S., Subrata, I.D.M., Supandi, Alatas, H.
• Format: Article
• Language: English
• Subjects: Adaptive algorithm; Adaptive algorithms; Adaptive systems; Air monitoring; Air pollution; air pollution monitoring; Air quality; air quality monitoring; Airports; Algorithms; Cellular communication; Cost analysis; Data transmission; Environmental monitoring; Gas detectors; Graphical user interface; low-cost sensors; Metal oxides; Microcontrollers; Monitoring; Monitoring systems; Nitrogen dioxide; Outdoor air quality; Particulate emissions; Pollutants; Pollution measurement; Pollution monitoring; Rechargeable batteries; Sensor systems; Sensors; Service modules; Signal strength; Sulfur dioxide; Temperature sensors
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2022.3222329

Air pollution is a significant concern in this era. Pollutants released in large quantities can cause environmental damage and human health problems. The existing monitoring systems are highly precise and sensitive, but they require high laboratory analysis and operational costs. To overcome these problems, an air quality monitoring system is proposed as an alternative solution that can complement the current system. This study aimed to design an inexpensive air quality monitoring system using metal oxide sensors to measure the concentrations of carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter (PM) using laser diffraction, microcontroller, and General Packet Radio Service (GPRS) module. The Air Quality IPB Monitoring System (AQIMoS) is powered by a rechargeable battery that is supplied by either a solar panel or AC power supply. AQIMoS is equipped with an information system, namely, a server and a graphical user interface, to receive data, calculate the air pollutant standard index (ISPU), and access data. This study also developed an algorithm to reduce packet loss in cellular network-based transmissions. This algorithm allows AQIMoS to perform repeated data transmissions and extend response waiting times according to a received signal strength indicator (RSSI). The test results show that the developed algorithm can reduce packet loss by 9.8-11.6 % in medium/bad conditions (MB, signal < 50%). The AQIMoS test was carried out in a traffic-heavy area about 2 km from Atang Senjaya Airport with moderate air quality.