Estimating particulate matter using COTS cameras

Hsin Hung Hsieh, Hu Cheng Lee, Wen Liang Hwang, Ling-Jyh Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Particulate pollution has become increasingly critical and threatening for human health. Although a number of approaches have been attempted for particulate pollution monitoring, these approaches are either expensive, unscalable, or requiring deployment of yet-another sensing infrastructure. In this study, by combining the advanced image dehazing and support vector machine techniques, we propose a novel particulate matter sensing approach using commercially off-the-shelf cameras. Using a Raspberry Pi-based testbed, we conducted a half-year measurement and conduct a comprehensive analysis of our approach. We show that our approach is effective, and the 80%-th estimation error is below 20 and 30 μg/m3 for PM2.5 and PM10 estimation, respectively. Moreover, the proposed approach can be easily applied to the existing camera surveillance infrastructure, as long as the photos contain both long-range and near-view objects.

Original languageEnglish
Title of host publication2015 IEEE SENSORS - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479982028
DOIs
Publication statusPublished - 2015 Dec 31
Event14th IEEE SENSORS - Busan, Korea, Republic of
Duration: 2015 Nov 12015 Nov 4

Publication series

Name2015 IEEE SENSORS - Proceedings

Other

Other14th IEEE SENSORS
CountryKorea, Republic of
CityBusan
Period15/11/115/11/4

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ASJC Scopus subject areas

  • Instrumentation
  • Electronic, Optical and Magnetic Materials
  • Spectroscopy
  • Electrical and Electronic Engineering

Cite this

Hsieh, H. H., Lee, H. C., Hwang, W. L., & Chen, L-J. (2015). Estimating particulate matter using COTS cameras. In 2015 IEEE SENSORS - Proceedings [7370683] (2015 IEEE SENSORS - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSENS.2015.7370683