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Measurement Uncertainty Evaluation for Sensor Network Metrology
by
Peter Harris, Peter Friis Østergaard, Shahin Tabandeh, Henrik Söderblom, Gertjan Kok, Marcel van Dijk, Yuhui Luo, Jonathan Pearce, Declan Tucker, Anupam Prasad Vedurmudi and Maitane Iturrate-Garcia
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Abstract
Sensor networks, which are increasingly being used in a broad range of applications, constitute a measurement paradigm involving ensembles of sensors measuring possibly different quantities at a discrete sample of spatial locations and temporal points outside the laboratory. If sensor networks are to
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Sensor networks, which are increasingly being used in a broad range of applications, constitute a measurement paradigm involving ensembles of sensors measuring possibly different quantities at a discrete sample of spatial locations and temporal points outside the laboratory. If sensor networks are to be considered as true metrology systems and the measurement results derived from them used for decision-making, such as in a regulatory context, it is important that the results are accompanied by reliable statements of measurement uncertainty. This paper gives a preview of some of the work undertaken within the European-funded ‘Fundamental principles of sensor network metrology (FunSNM)’ project to address the challenges of measurement uncertainty evaluation in some real-world sensor network applications. The applications demonstrate that sensor networks possess features related to the nature of the measured quantities, to the nature of the measurement model, and to the nature of the measured data. These features make conventional methods of measurement uncertainty evaluation, and established guidelines for measurement uncertainty evaluation difficult to apply. An overview of some of the modelling tools used to address the challenges of measurement uncertainty evaluation in those applications is given.
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