Work

Gaussian processes and sensor network calibration

Year: 2024

Type: article

Abstract: Sensor networks provide a new measurement modality addressing the measurement requirements of societal challenges relating to climate change and environment, for example. In this paper, we first discuss issues with applying the GUM uncertainty framework to uncertainty quantification for sensor network measurements. We then discuss the calibration of the sensors in situ by exploiting the spatio-temporal correlation in the signal being measured. In particular, we look at collocation experiments in which a number of reference and test sensors are located in proximity so that the test sensors can be calibrated against the reference sensors.

Source: Measurement Sensors

DOI: 10.1016/j.measen.2024.101512

Authors: João A. Sousa, Alistair B. Forbes

Institutions: Instituto Português Da Qualidade, National Physical Laboratory

Language: English

Topic: Scientific Measurement and Uncertainty Evaluation

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $1,800

OpenAlex ID: W4405798451

FWCI: 0.278

Cites: 22

Cited by: 1

Related to: 10