Information leveraged from multiple sensors is generally more versatile than that from a single sensor. For instance, the value of a physical quantity at an unsampled location can be estimated by interpolating measurements from spatially separated sensors. In this contribution, kriging is used to spatially interpolate room temperatures from a limited number of sensors with different measurement uncertainties and a propagation of the sensor uncertainties to the interpolated values using a Monte Carlo simulation is demonstrated. A potential application of kriging to assess the quality of sensor measurements is also presented.

The Metrology Cloud has been described and implemented at some degree for several National Institutes of Metrology (NMI) or Designated Bodies, typically with emphasis in the Legal Metrology aspects, however, there is a lack of coverage for Scientific Metrology aspects. The paper first describes the situation at a specific NMI, then details the used procedure to find a solution and briefly provides examples for time conditioned properties, time dependent behavior, and virtual measuring instrument’s simulated response, finally the results are revised, and future work is listed besides conclusion.

As part of the digital transformation the usage of sensor networks is rapidly increasing. Metrological applications at the NMI level can benefit from this new technology as well. In this manuscript we report on a sensor network that was installed in VSL’s length laboratory to measure in more detail the ambient temperature profile as required for measuring long distances by an interferometric application. The measurement results of the sensor network were compared with the results from the 5 sensors that have been used until now. An offset in the mean temperature of about 0.2 ◦C was found, which was just about the maximum allowed bias in view of the claimed uncertainty for the distance measurement. At a more general level, it was concluded that such sensor networks provide a useful new tool to increase the understanding of other measurements, to validate assumptions and possibly optimize existing measurements.

The digital transformation has emerged to be a novel concept in recent times with numerous innovative advantages and some associated unpredictable risks like cyber security, data encryption, data storage and secured communication etc. It is a multifaceted and emerging phenomenon that has significant impact and is this essentially required in the industrial sector for taking the advantages of cutting-edge technologies and internet of things so that the machine can communicate with the outer word in real-time mode. The main objective of this paper is to understand and analyze the effects of digital transformation in metrological sector and its relevance and suitability for the industrial and economic growth. There have been various innovative frameworks developed and reported in recent times employing the various novel tools like digital and smart sensing, rapid prototyping, risk analysis and mitigation, real time data analysis, cyber security, cloud development and Internet of Things etc. Machine learning, artificial intelligence and cybersecurity are the main support systems of developing digital transforming capabilities. The key benefits of digital transformation are the sustainable development and economic growth of any manufacturing unit which indirectly related to the improvement in the overall performance of the retail sector. It is thus the need of hour to focus and implement these aspects in developing a national digital quality infrastructure for augmenting the economic and industrial growth of India.

Product certifications are conformity assessments for items. In the testing for the product certification, the managerial and technical procedures are validated through another conformity assessment, the accreditation of the testing laboratory. The review for the accreditation is implemented once a few years. The digitalized history of the laboratory activities (e.g. the external and internal reviews, the training, and the calibrations) can be helpful to check the quality of the testing for individual product certifications. In this report, we discuss what data has to be assessed and how security mechanisms can be implemented.