Sensors, Vol. 18, Pages 4380: Calibration Model of a Low-Cost Air Quality Sensor Using an Adaptive Neuro-Fuzzy Inference System

Sensors, Vol. 18, Pages 4380: Calibration Model of a Low-Cost Air Quality Sensor Using an Adaptive Neuro-Fuzzy Inference System Sensors doi: 10.3390/s18124380 Authors: Kemal Maulana Alhasa Mohd Shahrul Mohd Nadzir Popoola Olalekan Mohd Talib Latif Yusri Yusup Mohammad Rashed Iqbal Faruque Fatimah Ahamad Haris Hafizal Abd. Hamid Kadaruddin Aiyub Sawal Hamid Md Ali Md Firoz Khan Azizan Abu Samah Imran Yusuff Murnira Othman Tengku Mohd Farid Tengku Hassim Nor Eliani Ezani Conventional air quality monitoring systems, such as gas analysers, 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. One possible solution to complement these techniques is the application of low-cost air quality sensors (LAQSs), which have the potential to give higher spatial and temporal data of gas pollutants with high precision and accuracy. In this paper, we present DiracSense, a custom-made LAQS that monitors the gas pollutants ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). 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. Laboratory calibrations were carried out to determine the zero offset and sensitivities of each sensor. The results showed that the sensor performed with...
Source: Sensors - Category: Biotechnology Authors: Tags: Article Source Type: research