Stochastic Online Calibration of Low-Cost Gas Sensor Networks With Mobile References

Abstract

There has been a wide interest in high-resolution air quality monitoring with low-cost gas sensor systems in the last years. Such gas sensors, however, suffer from cross-sensitivities, interferences with environmental factors, unit-to-unit variability, aging, and concept drift. Therefore, reliability and trustworthiness of the measurements in the low parts-per-billion (ppb) range remain a concern, particularly over the course of the lifetime of a sensor network in urban environments. In this simulation study, the possibility to continuously recalibrate a wireless sensor network with mobile references and stochastic gradients computed from encounters is explored. By using data collected in field experiments, encounters between static and mobile nodes are modeled as a probabilistic process. Moreover, the influence of a collection of design parameters such as base calibration, initial recalibration, choice of optimization algorithm, as well as encounter frequency are analyzed and discussed. With an optimized protocol, it can be shown that long-term reliable measurements with absolute errors of about 50 ppb for CO, 3 ppb for NO 2 , and 4 ppb for O 3 could be achievable with a few mobile references in urban environments.

Temporal Pattern-Based Denoising and Calibration for Low-Cost Sensors in IoT Monitoring Platforms

“…Cui et al [20] propose that, after in-situ calibration, sensors should be recalibrated using mobile instruments that are brought close to the sensor location for a period of time. Tancev et al [21] install reference instruments in arbitrary vehicles and recalibrate the LCSs when the vehicles are in proximity to the sensors.…”

Effect of Three-Dimensional-Printed Thermoplastics Used in Sensor Housings on Common Atmospheric Trace Gasses

“…These sensors offer a cost-effective, compact, portable alternative to traditional monitors. Additionally, low-cost sensors have enabled the creation of large sensor networks that augment established government monitoring sites and increase the spatial distribution of measurements [ 5 , 6 , 7 , 8 ]. Simultaneously, 3D printing, particularly fused deposition modeling (FDM) using thermoplastic filaments, has emerged as an economical means to craft customized structural supports and sensor housings for air quality research applications [ 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ].…”