Publication Type
Journal Article
Version
acceptedVersion
Publication Date
7-2018
Abstract
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.
Keywords
Sensor calibration, low cost sensors and devices, air pollution sensors, air quality sensor networks
Discipline
Environmental Sciences | Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
IEEE Internet of Things
Volume
5
Issue
6
First Page
4857
Last Page
4870
ISSN
2327-4662
Identifier
10.1109/JIOT.2018.2853660
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
MAAH, Balz; ZHOU, Zimu; and THIELE, Lothar.
A survey on sensor calibration in air pollution monitoring deployments. (2018). IEEE Internet of Things. 5, (6), 4857-4870.
Available at: https://ink.library.smu.edu.sg/sis_research/4533
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/JIOT.2018.2853660