This paper discusses the deployment of an internet of things (IoT)-based model to monitor the fermentation of tea in a tea factory in Kenya. The model uses deep learning to detect the optimum fermentation of tea as fermentation progresses. To further improve on the results, a majority voting technique based on regions is used. The model shows promising results, and its predictions correlated well with those of the experts.

We propose a surface plasmon resonance (SPR) sensor based on a ZnO / Au hybrid thin-film material structure and experimentally investigate its sensitivity improvement. The Kretschmann-based SPR sensor utilizes ZnO thin films and nanostructures for performance enhancement. The advancement in SPR technology relies on a low-cost, high-sensitivity, and high-selectivity sensor. Metal oxide (MO) has been incorporated into the SPR sensor to be used for detection of biological and chemical compounds.

A new metrological atomic force microscope (MAFM) head design is shown. We investigated the MAFM head in the nanomeasuring machine (NMM-1) for different high-precision and large-scale traceable measurement tasks. Due to their integration, the MAFM head can benefit from the large measuring range, high-precision and traceability of the NMM-1 for efficient measurements on different samples. The presented results show the realised macroscale measurements with sub-nanometre resolution.

In thermometry, the displayed temperature value of an object depends on the size of the object. This behaviour, the size-of-source effect, might be a major cause of measurement uncertainty in a thermoscene. The influence of diffraction and digitization can be described advantageously with the modulation transfer function. Especially with very small objects the displayed temperatures are too low. When imaging large objects, not only the edge areas are affected, but also the entire image.

Detection of flammable gases is necessary to avoid explosive atmospheres. Commercial pellistors require an operation temperature above 450 °C for the detection of methane. We present a novel wireless low-power catalytic gas sensor system based on non-precious metal catalyst for the detection of methane and propane operated at 350 °C. The combination of a MEMS-based sensor with a low-power radio system provides the opportunity to monitor complex infrastructures without using a power grid.

A novel experience replay particle swarm optimization algorithm is presented and successfully deployed to improve the optimization performance for reconfigurable analog integrated circuits of industry 4.0. An optimization approach is introduced that relied on THD-based indirect measurement method that varies from the traditional calibration approach. Instead, the proposed calibration methodology optimizes all characteristics of the reconfigurable amplifier at once.

During the geometric calibration of infrared cameras, the parameters that describe where object points are mapped onto thermal images are determined. The required reference data is obtained by capturing so-called calibration targets. In established approaches, it is difficult to estimate the lens distortions precisely. A newly developed target and its evaluation algorithm make it possible to increase the sensitivity of the calibration by finding reference points close to image borders.

The publication contributes to a uniform procedure for in-process measurement data acquisition in additive manufacturing, which is essential for a controlled correction of detected manufacturing deviations. The developed methodology is based on an analysis of the melt pool contours relative to a referencing system integrated in the powder bed. By recording the referenced melt pool and the shimmering contours after powder application, manufacturing deviations can be evaluated more accurately.

Synchronization problems within distributed sensor networks are a major challenge in the field of Industry 4.0. In this paper, artificially generated time shifts between sensor data and their influence on remaining useful lifetime prediction of electromechanical cylinders are investigated. It is shown that time shifts within sensor data lead to poor remaining useful lifetime predictions. However, this prediction can be significantly improved using various methods as shown in this contribution.

In order to contribute to a standardisation and process monitoring of additive manufacturing (AM) processes, a novel referencing approach was developed to improve the assessment of geometric manufacturing and measurement deviations. This is based on a referencing system integrated in the powder bed, which enables a shortening of the measuring loop. The position-stable quartz glass pipes enable more precise specification of lateral manufacturing and measurement deviations during AM.

The development of optical design is characterized by the desire for more applications and better performance. The latest result of this development is freeform optics offering almost unlimited possibilities for the designers. However, an optical component has also to be manufactured and tested by metrology. We propose a measurement technique for the surface characterization of freeform optical components and highlight the possible error sources and their influence on the measurement result.

Temperature sensors based on piezoelectric devices enable precise measurement of temperature changes in harsh environments such as high temperatures or aggressive atmospheres. In the case of this device, the change in the temperature is detected by means of the changing resonance frequency of the sensor. Here a sensor device based on catangasite (an isomorph of quartz) is presented. We discuss its behavior at elevated temperatures and confirm that it can successfully operate up to 1030 °C.

A homemade experimental setup was developed using actuators and temperature sensors monitored by Arduino platforms to characterize thermal behaviors of composite panels containing phase-change materials (PCMs). The characterization is based on modeling steady-state thermal conduction and natural convection heat transfer. Temperature measurements allow for obtaining effective thermal conductivity, phase shift time, and energy storage capacity of composite panels incorporating PCMs.

The paper presents a concept for an automated classification of machine-readable data from measurement according to its agreement with metrological guidelines. An implementation of the classification was realized within the TraCIM online validation system for trustworthy certification of software that is under quality management. The research was collaboratively made by the partners of the European Metrology Research Project SmartCom.