IoT systems based on collaborative sensor networks are becoming increasingly common in various industries owing to the increased availability of low-cost sensors. The quality of the data provided by these sensors may be unknown. For these reasons, advanced data processing and sensor network self-calibration methods have become popular research topics. In terms of metrology, the self-calibration methods lack the traceability to the established measurement standards of National Metrology Institutes (NMIs) through an unbroken chain-link of calibration. This problem can be solved by the ongoing digitalization of the metrology infrastructure. We propose a conceptual solution based on Digital Calibration Certificates (DCCs), Digital SI (D-SI), and cryptographic digital identifiers, for validation of data quality and trustworthiness. The data that enable validation and traceability can be used to improve analytics, decision-making, and security in industrial applications. We discuss the applicability and benefits of our solutions in a selection of industrial use cases, where collaborative sensing has already been introduced. We present the remaining challenges in the digitization and standardization processes regarding digital metrology and the future work required to address them.

In rotating machinery, excessive vibration can affect the lifetime of the machine and, for example, in paper machines, it can directly affect production quality. Hence, it is important to monitor vibrations. Typically the vibrations are measured with piezo-based accelerometers attached to the bearing housing. Installation of the accelerometers and especially cabling is laborious and expensive in the case of existing machines that have several components to monitor. In continuous process maintenance, a break may be required as well. Therefore, typically only the critical rotors will be monitored, if at all. This research focuses on applying wireless microelectromechanical systems (MEMS) accelerometers to the measurement of large rotor vibration. The results indicated that MEMS accelerometers combined with wireless communication can offer a viable alternative to more expensive piezo-based accelerometers with traditional wire-based communication. The combination provides a flexible and cost-effective method for the collection of vibration data from large rotors and rotor systems.

Internet of Things (IoT) device data enables diverse applications. However, the quality of data are non-standardized and difficult to quantify. While poor quality data may be usable, establishing error bounds supports IoT's use in critical applications. National Metrology Institutes (NMIs) have long tradition in making measurement data trustworthy, and they are now working to digitalize these practices. This paper forwards that agenda by presenting a Distributed Ledger Technology (DLT) based concept to leverage digital metrology for IoT data and devices. Digital Calibration Certificates (DCCs) offer a solution for describing, certifying, authenticating, and securing IoT data quality. With DCCs, measurement device (sensor) calibration information may be included as metadata alongside samples captured by a device. Metadata may include device identification, which serves as proof-of-origin for measurements and samples, and timing data, to ensure its “freshness.” DCCs enhance communicating the quality of captured information among devices, services, and applications, thereby supporting IoT's use in domains with strict error constraints. Our proposed concept securely validates DCC-based (meta)data traceability chain from NMIs and devices to data end-users with cryptographic measures, rendering IoT data trustworthy for critical applications.