This contribution deals with the exploration of human–robot collaboration using an infrared sensor and artificial intelligence (AI) to improve the safety and efficiency of the collaboration. The main contribution is the unique thermal dataset WLRI-HRC generated in a manufacturing environment and the evaluation of the dataset using different AI network methods.

We present a sensor platform that can detect the oral cancer signature of biomarkers in saliva. This system works by arraying metal–oxide–semiconductor field-effect transistors (MOSFETs) and electrolyte-gated transistors (EGTs), with each targeting a biorecognition element (BRE) from a DNA sequence found in the promoter region of most biomarker genes. This system is also applicable to the simultaneous diagnosis of TNF-α and IL-1β immune-modulator biomarkers.

Continuous quality monitoring has become increasingly important in industrial processes, such as raw-milk monitoring. This can often be achieved by detecting individual process markers in the gas phase, which requires inexpensive analytical systems. Therefore, an easy-to-implement three-step concept has been developed that aims to bring together the chemical–analytical and sensor–technical sides. This concept is designed to be applicable in a wide variety of cases and to a range of sensors.

In the context of climate change adaptation of cities to mitigate heat stress, citizen participation is a promising approach. A densely distributed measurement network of 59 quality-controlled meteorological low-cost sensors was set up in an urban study area in Pune for continuous data collection by engaging local communities. Analyses of measurements show the suitability of the monitoring network for scientific modelling applications and identify a high active interest of involved citizens.

The gas-sensing performance of the CuO/Cu₂O functionalized with Au NPs towards CO₂, CO, and HC_Mix was investigated by resistance measurement. The type of ligands has an impact on the sensing behaviour of CuO/Cu₂O sensors, and the highest response (39 %) for CO₂ is achieved by Au NPs stabilized with citrate. These differences in behaviour of the films depending on their ligands could be due to insufficient thermal degradation of the ligands.

Ferromagnetic materials change their magnetic properties under load, enabling the implementation of a force sensor. The magnetic field emerging from such a sensor can be measured by secondary sensors to approximate the load acting on the sensor. A test setup simulating a potential application environment is described and its measurement results are presented. Furthermore, relevant magnetic material properties of an exemplarily chosen cold working steel are discussed.

Some air pollution gases, such as nitrogen dioxide, are toxic at very low concentrations, highlighting the need for extensive research on materials with high sensitivity. Carbon nanotubes are nanomaterials capable of sensing toxic gases in very low concentrations. Their integration into sensors remains challenging, due, in part, to their small dimensions. This work represents a study that tests a method of safely and efficiently localizing carbon nanotubes for their integration into sensor devices.

Continuous odor monitoring is becoming increasingly important. Therefore, odor monitoring systems are needed that are less expensive than conventional laboratory equipment and do not require trained personnel. Here, a gas chromatography selective odorant measurement sensor array (GC-SOMSA) system is used as part of the development concept. It correlates a sensor response to a mass spectrometer signal and an odor impression. This allows for a fast and inexpensive characterization suitable for many applications.

Microelectromechanical systems mirrors are used in applications such as projection, biological imaging, and light detection and ranging due to their compact size, affordable price, and low power consumption. Piezoelectric actuation with lead zirconate titanate offers high force and fast response but raises environmental concerns due to its lead content. Potassium sodium niobate is a promising lead-free alternative, exhibiting high performance on 200 mm silicon substrates.

Selecting the best model for monitoring industrial machines is challenging due to limited data and varying conditions. While deep learning (DL) is often considered ideal, it does not always perform well. We compared DL with traditional methods focused on feature extraction and classification. Our tests on seven datasets revealed that traditional methods are more reliable when machine conditions change, highlighting the importance of simpler, interpretable models for industrial monitoring.

A simple physically motivated model for measurements obtained by nondestructive testing and evaluation using eddy-current methods is created by using equivalent circuit networks that include all relevant effects. The transfer function of a network is derived and its physical meaning discussed. For use in process control, a sensor system with low-latency parameter identification is integrated into a forming process, and its abilities to monitor microstructure changes are demonstrated.

Photo-thermal actuation and laser Doppler vibrometry enable fast, contactless characterization of MEMS (microelectromechanical system) resonators already before electrical connections are made. This paper details a tailored setup combining a precision stage, vacuum chamber, laser diode, and vibrometer to analyze silicon MEMS devices on a wafer level. Tests reveal how silicon device layer thickness affects resonance frequency and identify dominant loss mechanisms in different vibrational modes.

To improve the accuracy of polarization random noise signal recognition and the noise suppression effect, a polarization random method of noise suppression in a two-dimensional force sensor based on random forest is proposed.

A simple and cost-effective MIP-based sensing system for the colorimetric detection of 2-methoxphenidine (2-MXP) was demonstrated. Unlike typical colorimetric systems that rely on spectrometers, this system utilizes an RGB sensor and an LED. Constructed from readily available commercial components, it can be manufactured in a standard lab environment. The system detects 2-MXP in aqueous solutions at concentrations below 1 mM and can distinguish between concentrations of 1, 0.5, 0.25, and 0.1 mM.

We developed a measurement system to improve sand core production in foundries. Sand cores are essential for creating complex shapes in metal casting. Our system uses ultrasound waves to monitor the curing process, indicating how much of the catalyst remains in the exhaust gas. This real-time monitoring allows manufacturers to optimize the process, reducing waste and enhancing product quality. We tested the system on a lab-scale core-making machine and demonstrated its effectiveness.

Robust and interpretable machine learning algorithms, which have been proven in various applications, often lack efficient implementation on limited hardware. The novel approach is to convert the inference of the interpretable ML into a deep neural network, which is efficiently executable on edge hardware. This approach was validated in terms of runtime efficiency, memory requirements, and accuracy and resulted in a significant improvement in terms of runtime and memory requirements.

We present a sensor with an original architecture for gas sensing that is 4 times more efficient than other sensors based on the same detection technology. It has a small volume (less than 1 cm³), low cost, and low power consumption, making it possible for it to be used in compact systems and even in smartphones. It is able to detect small changes in carbon dioxyde concentrations in ambient air for indoor air quality monitoring.

Globally, water has been the cause of the rise of civilization and also a cause of conflict. In this changing climate, managing water, the most precious commodity, has become a necessity. If we want to manage a resource properly, we need technology and data. With the innovative WAMO 300, a decentralised solution for this problem has been provided. WAMO 300, short for Water Monitor 300, acts as an IoT (Internet of Things) system that brings data from the physical world to the digital world.

We present a new method for creating flexible temperature sensors that can be applied to complex shapes. By using a technique called water transfer printing, these sensors can be transferred directly onto surfaces without the need for flexible films . This allows them to be more accurate, more reliable, and more adaptable than traditional sensors.  These sensors can work well in various environments and are unaffected by humidity, making them ideal for use in healthcare, robotics, and wearable devices.

In this study, we consider the planform of a cantilever piezoelectric vibrating energy harvester (PVEH) device in which the inertia of the cantilever itself is dominant relative to the inertia of an edge block. We derive the optimal planform which ensures the harvested energy is maximal. We show that the contours of the optimal planform are defined by Bessel functions. The predictive capabilities of our model are demonstrated by comparison to finite-element simulations.

In many investigations of piezoelectric energy harvesters, it is often tacitly assumed that optimal performance is achieved when the vibration mode of the structure ensures a uniform strain within the piezoelectric layer. This manuscript provides, for the first time ever, a rigorous proof of this point.

In a miniaturized gas chromatography system, there could be identification doubt between compounds eluting at close retention times. When a sensor is a thermal conductivity detector (TCD), we investigated a double-measurement approach (two temperatures) to improve specificity. Unfortunately, both theory and experiments showed that this method could only work for relatively high compound concentrations (1–50 ppm). This is therefore not relevant for a trace analysis system (1–10 ppb).

This project developed a low-cost, real-time portable device for measuring radiation. The device is based on a camera similar to those used in modern smartphones and includes the ability to connect to the internet, allowing users to access data through any web browser. The program files are available for download for educational purposes.