Improving Low-Cost Carbon Dioxide Sensor Accuracy for Environmental Air Quality Monitoring Systems

The majority of human beings spend their time indoors. However, the quality of indoor air is worse when compared to that of outdoor air. Air pollution can lead to inadequate indoor air quality, which can have both direct and indirect impacts on the health of the occupants of the building. Exposure to air pollution over a prolonged period or through indirect means can potentially lead to illness. Carbon dioxide is one of the pollutants present in the air. The Internet of Things has been utilized to conduct extensive research on measuring carbon dioxide levels. The CCS811 is a digital gas sensor with ultra-low power consumption, commonly utilized for monitoring carbon dioxide levels. However, it is necessary to calculate and enhance the accuracy of the sensor. The purpose of this research is to calculate and enhance the accuracy of low-cost carbon dioxide sensors used in ambient air quality monitoring systems. The approach entails the measurement of carbon dioxide concentration in a room, followed by a comparison of the obtained result with a calibrator. The linear regression model is used to modify the IoT source code in order to enhance accuracy. After the calibration process, the accuracy has improved from 92.67 percent to 95.26 percent.