Electrical Engineering, Indian Institute of Technology, Madras 600036, India.
Civil Engineering, Indian Institute of Technology, Madras 600036, India.
Sensors (Basel). 2022 Jan 5;22(1):394. doi: 10.3390/s22010394.
Low-cost sensors (LCS) are becoming popular for air quality monitoring (AQM). They promise high spatial and temporal resolutions at low-cost. In addition, citizen science applications such as personal exposure monitoring can be implemented effortlessly. However, the reliability of the data is questionable due to various error sources involved in the LCS measurement. Furthermore, sensor performance drift over time is another issue. Hence, the adoption of LCS by regulatory agencies is still evolving. Several studies have been conducted to improve the performance of low-cost sensors. This article summarizes the existing studies on the state-of-the-art of LCS for AQM. We conceptualize a step by step procedure to establish a sustainable AQM setup with LCS that can produce reliable data. The selection of sensors, calibration and evaluation, hardware setup, evaluation metrics and inferences, and end user-specific applications are various stages in the LCS-based AQM setup we propose. We present a critical analysis at every step of the AQM setup to obtain reliable data from the low-cost measurement. Finally, we conclude this study with future scope to improve the availability of air quality data.
低成本传感器 (LCS) 因其能够以低成本实现高时空分辨率，且易于实现公民科学应用（如个人暴露监测），而在空气质量监测 (AQM) 中越来越受欢迎。然而，由于 LCS 测量中涉及到各种误差源，其数据的可靠性值得怀疑。此外，传感器性能随时间的漂移也是一个问题。因此，监管机构对 LCS 的采用仍在不断发展。已经进行了一些研究来提高低成本传感器的性能。本文总结了现有的关于用于 AQM 的低成本传感器的最新研究。我们提出了一个逐步的步骤，以建立一个使用 LCS 能够产生可靠数据的可持续 AQM 设置。我们提出的基于 LCS 的 AQM 设置中的各个阶段包括传感器的选择、校准和评估、硬件设置、评估指标和推断以及针对最终用户的应用。我们在 AQM 设置的每个步骤都进行了批判性分析，以从低成本测量中获得可靠的数据。最后，我们总结了这项研究的未来前景，以提高空气质量数据的可用性。
