Self-calibration methods for uncontrolled environments in sensor networks: A reference survey

Abstract

Growing progress in sensor technology has constantly expanded the number and range of low-cost, small, and portable sensors on the market, increasing the number and type of physical phenomena that can be measured with wirelessly connected sensors. Large-scale deployments of wireless sensor networks (WSN) involving hundreds or thousands of devices and limited budgets often constrain the choice of sensing hardware, which generally has reduced accuracy, precision, and reliability. Therefore, it is challenging to achieve good data quality and maintain error-free measurements during the whole system lifetime. Self-calibration or recalibration in ad hoc sensor networks to preserve data quality is essential, yet challenging, for several reasons, such as the existence of random noise and the absence of suitable general models. Calibration performed in the field, without accurate and controlled instrumentation, is said to be in an uncontrolled environment. This paper provides current and fundamental self-calibration approaches and models for wireless sensor networks in uncontrolled environments.

Ground Level Ozone Formation Near a Traffic Intersection: Lisbon “Rotunda De Entrecampos” Case Study

“…Peterson et al 2017 [28] shows scatter plots of raw output voltage and NO 2 concentration (µg/m 3 ). Barcelo-Ordinas et al 2019 [29] deals with the calibration of sensor networks in uncontrolled environments. Data faults (data reported by a sensor that is inconsistent with the phenomena of interest) can happen due to environmental noise, the precision of the equipment, and manufacturing defects.…”

A Comparative Study of Calibration Methods for Low-Cost Ozone Sensors in IoT Platforms

“…There has recently been a large number of studies devoted to calibration in many fields related to low-cost sensor in IoT platforms including weather, air quality monitoring, target discovery, synchronization or localization [6]. Signal processing techniques have been applied to calibrate low-cost sensors in IoT.…”

“…Several authors [10], [17], [18] have shown that in order to calibrate air pollution sensors such as CO, NO 2 , CH 4 , O 3 , CeO 2 or C 3 H 8 it is needed an array of sensors. The idea of sensor array calibration consists in measuring all the cross-sensitivities to compensate for all interfering pollutants and environmental conditions [5], [6]. For example, to calibrate a NO 2 sensor, NO 2 , O 3 , temperature, and relative humidity are measured.…”

“…There are several calibration approaches to calibrate a sensor node [6]. The most typical is the approach in which uncalibrated sensor nodes are collocated (placed) a few meters away from the reference node [11], [12].…”

“…Many of the low-cost sensors in IoT platforms are not calibrated by the manufacturers or if they are calibrated by them, the calibration has been done in laboratory chambers and not in the environmental conditions of the place where the nodes are deployed [3], [4]. In this case, the sensors of the IoT platform is calibrated during network deployment in an uncontrolled environment without laboratory instruments [5], [6].…”