2025 SMSI Bannerklein

A3.2 - Co-Calibration in Distributed Homogeneous Sensor Networks

Event
SMSI 2023
2023-05-08 - 2023-05-11
Nürnberg
Band
Lectures
Chapter
A3 - Metrology in the digital age
Author(s)
M. Gruber, S. Eichstädt, A. Vedurmudi - Physikalisch-Technische Bundesanstalt, Berlin (Germany)
Pages
47 - 48
DOI
10.5162/SMSI2023/A3.2
ISBN
978-3-9819376-8-8
Price
free

Abstract

Current work by the authors is focused on uncertainty-aware co-calibration of local homogeneous sensors, as well as spatial interpolation using machine-learning approaches. Requiring sensors to be quasi non-distributed is a strong assumption that greatly limits the potential applicability of co-calibration in practical scenarios. To overcome this limitation, it is shown that distributed sensors can provide virtual reference values by augmenting interpolation models with GUM uncertainty evaluation. Moreover, multiple interpolation models can be evaluated in parallel at a given spatio-temporal point, which can then be robustly combined via sensor fusion into a single virtual reference measurement. The approach is implemented inside a proof-of-concept simulation environment representing temperature sensors distributed inside a room.

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