Next Article in Journal
A Simple and Low-Cost Optical Fiber Intensity-Based Configuration for Perfluorinated Compounds in Water Solution
Previous Article in Journal
Label-Free Rapid Separation and Enrichment of Bone Marrow-Derived Mesenchymal Stem Cells from a Heterogeneous Cell Mixture Using a Dielectrophoresis Device
Previous Article in Special Issue
Energy Harvesting Sources, Storage Devices and System Topologies for Environmental Wireless Sensor Networks: A Review
Article Menu
Issue 9 (September) cover image

Export Article

Open AccessArticle
Sensors 2018, 18(9), 3008; https://doi.org/10.3390/s18093008

Sensor Selection to Improve Estimates of Particulate Matter Concentration from a Low-Cost Network

1
Department of Public Health, East Carolina University, Greenville, NC 27834, USA
2
Department of Occupational and Environmental Health, University of Iowa, Iowa City, IA 52242, USA
3
Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
4
Department of Industrial and Systems Engineering, University of Iowa, Iowa City, IA 52242, USA
*
Author to whom correspondence should be addressed.
Received: 6 July 2018 / Revised: 31 August 2018 / Accepted: 5 September 2018 / Published: 8 September 2018
(This article belongs to the Special Issue Sensor Networks for Environmental Observations)
Full-Text   |   PDF [2079 KB, uploaded 8 September 2018]   |  

Abstract

Deployment of low-cost sensors in the field is increasingly popular. However, each sensor requires on-site calibration to increase the accuracy of the measurements. We established a laboratory method, the Average Slope Method, to select sensors with similar response so that a single, on-site calibration for one sensor can be used for all other sensors. The laboratory method was performed with aerosolized salt. Based on linear regression, we calculated slopes for 100 particulate matter (PM) sensors, and 50% of the PM sensors fell within ±14% of the average slope. We then compared our Average Slope Method with an Individual Slope Method and concluded that our first method balanced convenience and precision for our application. Laboratory selection was tested in the field, where we deployed 40 PM sensors inside a heavy-manufacturing site at spatially optimal locations and performed a field calibration to calculate a slope for three PM sensors with a reference instrument at one location. The average slope was applied to all PM sensors for mass concentration calculations. The calculated percent differences in the field were similar to the laboratory results. Therefore, we established a method that reduces the time and cost associated with calibration of low-cost sensors in the field. View Full-Text
Keywords: PM; aerosol exposure; low-cost sensors; low-cost wireless network; occupational monitoring; sensor calibration; sensor selection PM; aerosol exposure; low-cost sensors; low-cost wireless network; occupational monitoring; sensor calibration; sensor selection
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

SciFeed

Share & Cite This Article

MDPI and ACS Style

Sousan, S.; Gray, A.; Zuidema, C.; Stebounova, L.; Thomas, G.; Koehler, K.; Peters, T. Sensor Selection to Improve Estimates of Particulate Matter Concentration from a Low-Cost Network. Sensors 2018, 18, 3008.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top