Detail Abstract

ASEAN Air Quality Monitoring Program Based on High Quality Low Cost Sensor

Abstract

Conventional air quality monitoring systems, such as gas analyzers, are commonly used in many developed and developing countries to monitor air quality. However, these techniques have high costs associated with both installation and maintenance. ASEAN countries need devices or equipment to monitor the air quality. One possible solution to provide such tools is the low-cost air quality sensors (LAQSs), which have the potential to give higher spatial and temporal data of gas pollutants and particulate matters with high precision and accuracy.<br> AirboxSense is a custom-made LAQS that monitors the gas pollutants ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO) as well as particulate matters (PM10 and PM2.5). The aim of this study is to investigate its performance based on laboratory calibration and field experiments. Several model calibrations were developed to improve the accuracy and performance of the LAQS. The results showed that the sensor performed with a highly linear correlation with the reference instrument with a response-time range from 0.5 to 1.7 min. The performance of several calibration models including a calibrated simple equation and supervised learning algorithms (adaptive neuro-fuzzy inference system or ANFIS and the multilayer feed-forward perceptron or MLP) were compared. Combinations of inputs were evaluated during the development of the supervised learning algorithm. The validation results demonstrated that the ANFIS model with four inputs had the lowest error in terms of statistical performance and the highest correlation coefficients with respect to the reference instrument (0.8 < r < 0.95). These results suggest that the developed low-cost air quality sensor with ANFIS model can be used as the air quality monitoring system and will serve as an alternative device for air quality monitoring throughout ASEAN countries.