Proceedings ArticleDOI
Low-cost air quality monitors: Modeling and characterization of sensor drift in optical particle counters
Michael Taylor
- pp 1-3
TLDR
In this article, the authors present a method for evaluating drift for inexpensive optical air quality sensors for mass deployment or personal use, where a total of 29 calibrated sensors were circulated through a public lending library over a period of approximately 7.5 months.Abstract:
Low-cost sensors for mass deployment or personal use must often be calibrated to account for poor mechanical and electrical tolerances. Equally important to the initial calibration, however, is the characterization of sensor drift. This paper presents a method for evaluating drift for inexpensive optical air quality sensors. A total of 29 calibrated sensors were circulated through a public lending library over a period of approximately 7.5 months. Following deployment, usage data was collected and each device was recalibrated. The resulting data is used to model drift as a function of time between calibration.read more
Citations
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Journal ArticleDOI
Field and Laboratory Evaluations of the Low-Cost Plantower Particulate Matter Sensor.
Misti Levy Zamora,Fulizi Xiong,Drew R. Gentner,Branko Kerkez,Joseph Kohrman-Glaser,Kirsten Koehler +5 more
TL;DR: Three Plantower PMS A003 sensors when exposed to eight particulate matter sources were evaluated and it was found that the sensors were most accurate for PM with diameters below 1 μm, and they poorly measured PM in the 2.5-5 μm range.
Journal ArticleDOI
Edge Computing Based IoT Architecture for Low Cost Air Pollution Monitoring Systems: A Comprehensive System Analysis, Design Considerations & Development
TL;DR: A novel approach to implement the air quality monitoring system, employing the edge-computing based Internet-of-Things (IoT) system, acquires a power consumption reduction up to 23% with a significant low cost.
Calibration and Characterization of Low-Cost Fine Particulate Monitors and their Effect on Individual Empowerment
TL;DR: The Speck fine particulate monitor as mentioned in this paper uses a Kalman filter with a piecewise sensing model to process data from a low-cost dust sensor using a KG filter.
Journal ArticleDOI
Evaluating the Performance of Using Low-Cost Sensors to Calibrate for Cross-Sensitivities in a Multipollutant Network.
Misti L. Zamora,Colby Buehler,Hao Lei,Abhirup Datta,Fulizi Xiong,Drew R. Gentner,Kirsten Koehler +6 more
TL;DR: In this article , a low-cost sensor network containing sensors for particulate matter, carbon monoxide, ozone, nitrogen dioxide, and nitrogen monoxide at a reference field site in Baltimore, MD, was used for training multiple regression models, and the second 6 months were used to evaluate the models.
Proceedings ArticleDOI
Advanced Data Processing for Communication-constrained Underwater Domain
TL;DR: A joint sensor selection and data recovery scheme using the independent thinning principle from Stochastic Geometry to transmit their data to the surface station and Total Variation Inpainting is applied to recover the entire data of the whole area from the available data.
References
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Proceedings ArticleDOI
A Low-cost Particle Counter And Signal Processing Method For Indoor Air Pollution
Michael Taylor,Illah Nourbakhsh +1 more
TL;DR: In this article, a very low-cost indoor monitor for measuring fine particulate matter using optical sensors and a unique data processing algorithm is presented, and the performance of the Speck alongside two professional handheld particle counters is examined.