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Alessia Gallerani, Marco Muzzarelli, Alberto Ferrari, Stefano Cattini, Luigi Rovati
Fluorescent Blood pCO2 Sensor with No Direct Blood–Fluorophore Contact: Real-Time Monitoring and Comparison with a Commercial Device

Continuous monitoring of blood pCO₂ in extracorporeal circulation (ECC) would significantly support clinical decisions. Unfortunately, this is generally not possible during routine ECC. One of the aspects that limits the possibility of monitoring blood pCO₂ in real-time is biocompatibility. This study investigates the performance of a “prototype” fluorescent pCO₂ sensor (MS2), designed exploiting a blood-compatible gas-permeable membrane to isolate the sensing chemistry from the patient’s blood and the “off-label” use of a commercial optical CO₂ sensor, namely, the MCR-O1P1C1 by PreSens. Unlike the PreSens sensor, which requires direct contact between the sensing element and the blood, the gas-permeable membrane of the MS2 creates a measuring chamber that isolates the sensing chemistry from the patient’s blood. During a 6.5-hour test with bovine blood, both sensors demonstrated suitable accuracy, matching the reference hemogas analyzer. While at present the MCR-O1P1C1 sensor provides shorter response times, the MS2 sensor potentially offers superior safety and biocompatibility compared to sensors that require contact between the sensing element and the patient's blood. These results position the MS2 as a promising solution for real-time, in-line blood gas monitoring in ECC procedures.

Alberto Vallan, Aurora Bellone, Guido Perrone, Marco Sento, Alessio Carullo
Calibration and Uncertainty Evaluation of Fiber Bragg Grating Temperature Sensors

The spectral response of Fiber Bragg Gratings (FBGs) is highly sensitive to temperature, making them ideal for sensors in industrial, structural, and medical applications. Although FBG thermometers are more expensive and require complex interrogation systems, their immunity to electromagnetic interference makes them the preferred option in challenging environments. In such cases, FBG sensors' unique benefits outweigh their typically lower accuracy. However, there are situations where high measurement accuracy is critical. This paper focuses on using FBG-based sensors for temperature measurements where accuracy is of primary concern. It outlines a calibration setup, analyzes uncertainty sources, and describes some contributions from both the thermal and optical components of the measurement system. Experimental results show that the performance of the interrogation system depends also on the FBG's characteristics and in some cases an independent calibration of the grating and system is not sufficient to assess the overall temperature uncertainty.

Marco Muzzarelli, Giovanni Gibertoni, Daniele Goldoni, Ali Marzdar, Enza Panzardi, Marco Grassi, Piero Malcovati, Marco Mugnaini, Luigi Rovati
Design Optimization of a Photoacoustic System for Gas Detection in Exhaled Breath

Exhaled breath analysis is a promising non-invasive approach for detecting disease-related biomarkers, including nitrogen dioxide (NO₂), which is associated with airway inflammation. A compact photoacoustic spectroscopy (PAS) system was developed using a 405 nm LED source and a resonant acoustic chamber optimized for NO₂ detection. Focused optical excitation enhances localized absorption, generating an acoustic signal detected by a MEMS microphone. The system demonstrated a good response to 50 ppm gas variation, supporting its suitability for low-cost breath analysis applications.

Maik Rosenberger, Mirco-Andy Eilhauer, Andrei Golomoz, Raik Illmann, Martin Richter, Richard Fütterer, Gunther Notni
Optical distance measurement for embedded programming and visualization in educational contexts

Nowadays, a multitude of sensors collect and process enormous amounts of measurement data. Depending on the complexity, these tasks are usually performed by microcontrollers, which read out the sensor data, pre-process it, and then transmit it to a PC, for example. Communication between the microcontroller and PC is often complex, but of central importance. Equally important is the subsequent processing and interpretation of the acquired measurement data. Using the example of an optical distance measurement, a hardware module was developed that can establish an interface to a measuring computer via a microcontroller. In this system, care was taken to ensure that the embedded programming focused on pure C code, and that visualization is script-based in higher-level software. In this way, students learn how to use an embedded platform and an optical sensor, as well as how to further process data measurement on a control computer.

Chen Zhang, Wang Liao, Maik Rosenberger, Haoze Wang, Stephan Husung, Gunther Notni
Improvement of 3D shape measurement of translucent objects by applying direct-global light separation

This paper presents a novel approach for high-precision optical 3D shape measurement of translucent objects based on phase-shifting fringe pattern projection. To address the problem of subsurface scattering, the concept of separating direct and global light components is integrated into fringe projection to enable phase value recovery solely from direct light components. In the proposed approach, the fringe patterns are modulated with shifting perpendicular high-frequency stripes, and a sparsification of these fringe-stripe patterns is applied to reduce residual phase crosstalk. Furthermore, a method for the correction of phase jumping due to global illumination in gray code projection was developed. The 3D measurement of a translucent resin plate with aluminium regions validated this proposed approach. Compared to conventional fringe projection, the proposed method reduced the mean and maximal phase error by 62.2% and 52.5%, respectively, and the root mean squared error in the plane fitting using reconstructed 3D points of the plane object was reduced from 225.4 µm to 110.1 µm. These results confirm the potential of the developed technique for accurate 3D measurement of plastic materials and biological tissues.

Lennard Wunsch, Gunther Notni
Comparison of Principal Component Analysis and different band selection methods for classification of construction waste with hyperspectral images

This work presents a machine learning pipeline for construction waste sorting utilizing spectral imaging and comparing different dimensionality reduction methods. Aiming to correctly classify over 90% of objects in our dataset, we applied band selection methods based on Mutual Information, Fisher’s Score, Sequential Forward Selection, and Sequential Backward Selection. In addition, we examined Principal Component Analysis (PCA) and Categorical Maximum Spectral Difference. The performance of each pipeline is evaluated using metrics such as accuracy, precision, recall, F1 Score, and AUC-ROC.

Prabin Dhakal, Francesco Picariello, Basanta Joshi, Nanda Bikram Adhikari
Lightweight Passive Monitoring for Soft Anomaly Classification in Wired Networks on Resource Constrained Microcontrollers

This paper presents a method for detecting soft anomalies in Ethernet cables using time domain signal analysis and machine learning. A dataset consisting of oscilloscope captured signals from a CAT5e cable using passive measurement technique under four controlled scenarios was used. To reduce data dimensionality while preserving statistical characteristics, a histogram-based feature extraction process was applied prior to classification. Classification was performed using Decision Tree, Random Forest, and Support Vector Machine (SVM) algorithms under various downsampling rates. Models performances were good at generalizing and predicting the classes using those features. The results demonstrate that histogram features are effective in distinguishing between different anomaly types, even at significantly reduced sampling rates showing potential for real time implementation on low powered microcontroller platforms.

Clifford Brown, Julia Neumann
An Overview of Metrology Knowledge Storage: Taxonomies, Ontologies and Constrained Vocabularies

Within metrology new and innovative digital ways of working are being implemented that can offer great benefits to the future science, technology and administration of the area. How metrological knowledge is stored and hence processed will play an important role in maximizing the benefits of digitalisation. In this work a high level overview of current and future ways of storing scientific knowledge, the advantages and disadvantages are discussed. Finally, a potential optimal route to scientific knowledge storage for metrology is proposed.

Miguel Burg Demay, Luiz Eduardo de Farias, Gustavo Donatelli, Andre Luiz Meira de Oliveira
Enhancing digital twin reliability using FAIR principles and data quality assessment

The use of digital tools such as digital twins is spreading throughout the O&G sector. For integrity management, digital models of relevant asset degradation phenomena have been used to estimate and predict its health, aiming to improve maintenance planning and to provide information about the risk of failure and its evolution over time. The input data of models for O&G integrity monitoring are commonly found in different databases and present very different characteristics, such as sampling rate, temporal stability and variability, influencing the data quality in different ways. This work addresses the use of FAIR principles and data quality assessment for O&G asset integrity management. A brief review of established concepts is discussed, and a practical case study is presented, which illustrates the very important role that data quality assessment and the use of FAIR principles play in digital models’ reliability.

Matthias Prellwitz, Claudia Koch, Silke Richter, Johannes van de Kreeke, Michael Melzer, Mehran Monavari
The Digital Reference Material Document: From Paper Certificates to Interoperable Data Objects in Digital Quality Infrastructure

Reference materials (RMs) are essential for traceable and reliable measurements in science and industry, yet their certificate/document remain largely paper-based. The Digital Reference Material Document (DRMD) project at BAM introduces a transformative approach by converting traditional RM certificates/documents into machine-interpretable, XML-based digital assets. Building on the Digital Calibration Certificate framework, DRMDs encode ISO 33401 requirements and integrate semantic standards like D-SI and material identifiers. These digital documents support automated data exchange, integration into laboratory systems, and interoperability e.g. via asset administration shells and data spaces. The paper presents the DRMD schema concept, and outlines the path toward international harmonization and large-scale deployment, positioning DRMDs as a cornerstone of a digital quality infrastructure.

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