Ambient Air Monitoring System With Adaptive Performance Stability

Abstract

Air pollution is a significant concern in this era. However, large quantities of pollutants can cause environmental damage and human health problems. The existing monitoring systems are highly precise and sensitive; however, they require high laboratory analysis and high operational costs. To overcome these problems, an air quality monitoring system has been proposed as an alternative 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, a microcontroller, and a general packet radio service module. Our air quality index monitoring system is a sensor node powered by a rechargeable battery supplied by either a solar panel or an alternating current power supply. Our developed system is equipped with an information system, namely a server and graphical user interface, to receive data, calculate the air pollutant standard index, and access data. In this paper, we discussed a novel adaptive algorithm for reducing packet loss in cellular-network-based transmissions. This algorithm allows nodes to perform repeated data transmissions and extends the response waiting times according to the received signal strength indicator. The test results show that the developed algorithm can reduce packet loss by 9.8–11.6% under medium/bad conditions. The node test was carried out in a heavy traffic area approximately 2 km from Atang Senjaya Airport with moderate air quality.

Keywords

• Adaptive algorithm
• air pollution monitoring
• air quality monitoring
• low-cost sensors