Data Quality Characteristics for Improved Metrology in Sensor Networks

Mads Johansen, Anupam Prasad Vedurmudi, Martha Arbayani Zaidan, Milos Davidovic, Gertjan Kok, Maitane Iturrate-Garcia, Shahin Tabandeh
Abstract:
Sensor networks are becoming increasingly practical to deploy in largely varying settings, which combined with the growing availability of low-cost sensors and the increasing scale of sensor networks, makes it highly challenging to ensure the trustworthiness and reliability of measurements and data. Factors such as physical inaccessibility and cost constraints make it infeasible to use established methods for calibration, further increasing the difficulty of assessing measurement uncertainty and ensuring traceability in sensor networks. In addition, the large volume of data generated makes the assessment of data quality in sensor networks infeasible without automated, efficient, and reliable methods. This paper explores how well-known data quality characteristics can be applied in a metrologically sound manner, enabling quality assessments even when reference data or traditional calibration data are unavailable.
Download:
IMEKO-TC6-2025-060.pdf
DOI:
10.21014/tc6-2025.060
Event details
IMEKO TC:
TC6
Event name:
TC6 M4Dconf2025
Title:

2025 IMEKO TC-6 International Conference on Metrology and Digital Transformation

Place:
Benevento, ITALY
Time:
03 September 2025 - 05 September 2025