A survey on sensor calibration in air pollution monitoring deployments

• Main Authors: MAAH, Balz, ZHOU, Zimu, THIELE, Lothar
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Sensor calibration; low cost sensors and devices; air pollution sensors; air quality sensor networks; Environmental Sciences; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/4533; https://ink.library.smu.edu.sg/context/sis_research/article/5536/viewcontent/iotj18_maag.pdf
• Institution: Singapore Management University

Air pollution is a major concern for public health and urban environments. Conventional air pollution monitoring systems install a few highly accurate, expensive stations at representative locations. Their sparse coverage and low spatial resolution are insufficient to quantify urban air pollution and its impacts on human health and environment. Advances in lowcost portable air pollution sensors have enabled air pollution monitoring deployments at scale to measure air pollution at high spatiotemporal resolution. However, it is challenging to ensure the accuracy of these low-cost sensor deployments because the sensors are more error-prone than high-end sensing infrastructures and they are often deployed in harsh environments. Sensor calibration has proven to be effective to improve the data quality of low-cost sensors and maintain the reliability of longterm, distributed sensor deployments. In this article, we review the state-of-the-art low-cost air pollution sensors, identify their major error sources, and comprehensively survey calibration models as well as network re-calibration strategies suited for different sensor deployments. We also discuss limitations of exiting methods and conclude with open issues for future sensor calibration research.