Metrological Challenges in Collaborative Sensing: Applicability of Digital Calibration Certificates

Area of Science:

• Metrology
• Information Science
• Industrial IoT

Background:

• Industrial IoT systems increasingly rely on collaborative sensor networks with low-cost sensors.
• The data quality and traceability from these sensors are often unknown, posing challenges for industrial applications.
• Current self-calibration methods for sensor networks lack traceability to National Metrology Institutes (NMIs) standards.

Purpose of the Study:

• To propose a conceptual solution for validating data quality and trustworthiness in industrial IoT sensor networks.
• To address the lack of metrological traceability in current sensor network self-calibration methods.
• To leverage digitalization in metrology for enhanced data validation and industrial applications.

Main Methods:

• Conceptualizing a solution integrating Digital Calibration Certificates (DCCs), Digital SI (D-SI), and cryptographic digital identifiers.
• Developing a framework for data validation and traceability within collaborative sensor networks.
• Analyzing the applicability and benefits in industrial use cases with existing collaborative sensing.

Main Results:

• The proposed digital metrology solution enables validation of data quality and trustworthiness.
• The solution establishes an unbroken chain of traceability to established measurement standards.
• Improved data analytics, decision-making, and security in industrial applications are facilitated.

Conclusions:

• Digitalization of metrology infrastructure, through DCCs and D-SI, offers a viable solution for data quality and traceability in IoT.
• The proposed conceptual solution demonstrates significant benefits for industrial use cases.
• Further work is needed to address challenges in digitization and standardization for digital metrology.