TY - CONF A1 - Nattuveettil, Keerthana A1 - Brunner, Nanine A1 - Tiebe, Carlo A1 - Thomas, Marcus A1 - Melzer, Michael A1 - Bartholmai, Matthias A1 - Johann, Sergej A1 - Neumann, Patrick P. T1 - Digital approach of certification in Quality Infrastructure T2 - SMSI-2023-Proceedings / Chapter A3 - Metrology in the digital age N2 - QI-Digital is a joined project aiming at digitalising Quality Infrastructure (QI) processes involving standardization, conformity assessment, accreditation, metrology, and market surveillance [1]. Federal institute of material research and testing (BAM) is working on the creation of a digital calibration certifi-cate (DCC) to achieve digital metrological traceability and conformity assessment. The utilisation of machine readable and executable DCCs in the XML format is demonstrated on an example of a tem-perature measurement at a hydrogen refueling station. The certificates will be retrieved and analysed automatically at a Process Control System or at a Digital Twin. T2 - SMSI 2023 Conference CY - Nürnberg, Germany DA - 08.05.2023 KW - Quality Infrastructure KW - Digital Certificates KW - Temperature calibration KW - Digitalisation KW - Hydrogen technology PY - 2023 DO - https://doi.org/10.5162/SMSI2023/A3.4 SP - 51 EP - 52 PB - AMA Service GmbH CY - Wunstorf AN - OPUS4-57964 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Moufid, M. A1 - Tiebe, Carlo A1 - El Bari, N. A1 - Bartholmai, Matthias A1 - Bouchikhi, B. T1 - Advance in electronic nose technology developed for the detection and discrimination of ethanol, ammonia, and hydrogen sulfide gases T2 - IEEE International symposium on olfaction and electronic nose (ISOEN 2022) N2 - This work focuses on the design and fabrication of low-cost and fast-response of an electronic nose (E-nose) based on semiconductor gas sensors, for discriminating some synthetic gases such as ammonia (NH3), ethanol (C2H5OH), and hydrogen sulfide (H2S). Additionally, the capability of separating different concentration levels of each considered gases was checked. Dataset treatment of E-nose by using Principal Component Analysis (PCA) showed a good discrimination of the different synthetic gases. Furthermore, perfect classification was reached of different concentration levels of the analysed gases by using Discriminant Function Analysis (DFA). In the light of these results, it could be stated that the developed E-nose system constitutes an inexpensive, rapid, simple to use, and efficient tool for synthetic gases detection. T2 - IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) CY - Aveiro, Portugal DA - 29.05.2022 KW - Electronic nose KW - Metal oxide semiconductor KW - Chemometric techniques KW - Environmental analysis PY - 2022 SN - 978-1-6654-5860-3 DO - https://doi.org/10.1109/ISOEN54820.2022.9789636 SP - 1 EP - 3 AN - OPUS4-56574 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Moufid, M. A1 - Tiebe, Carlo A1 - El Bari, N. A1 - Hamada, D. A. A1 - Bartholmai, Matthias A1 - Bouchikhi, B. T1 - Pollution parameters evaluation of wastewater collected at different treatment stages from wastewater treatment plant based on E-nose and E-tongue systems combined with chemometric techniques JF - Chemometrics and Intelligent Laboratory Systems N2 - Wastewater contains harmful chemicals and heavy metals that are known to cause various environmental and health problems. Therefore, the water quality control using sensitive, simple, fast, accurate, and portable tools is of great importance. This study aimed to evaluate the pollution parameters of wastewaters collected at different treatment stages from a wastewater treatment plant (WWTP) that treats domestic and industrial wastewaters by using an electronic nose (E-nose) and a voltammetric electronic tongue (E-tongue) combined with chemometric techniques. Water and wastewater pollution parameters determination were performed using inductively coupled plasma optical emission spectrometry for the determination of cations, and anions by using ion chromatography. Chemometric techniques, such as Principal Component Analysis (PCA), Discriminant Function Analysis (DFA), Support Vector Machines (SVMs), and Hierarchical Cluster Analysis (HCA), were used to process the E-nose and E-tongue datasets to describe the similarities between the samples. In addition, Partial Least Squares Regression (PLSR) model was constructed using electronic sensing data to simultaneously predict the concentration values of physicochemical parameters. The obtained correlation coefficient, for training and testing sets, is higher than 0.91 for the prediction of the concentration of all physicochemical parameters, except for iron (Fe) which remains 0.84. These results suggest that simple, portable, and inexpensive tools such as electronic nose and tongue are suitable for wastewater analysis. KW - Wastewater KW - Electronic nose KW - Voltammetric electronic tongue KW - Water quality control KW - Chemometric techniques KW - Gas sensing PY - 2022 DO - https://doi.org/10.1016/j.chemolab.2022.104593 VL - 227 SP - 1 EP - 12 PB - Elsevier B.V. AN - OPUS4-55652 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Nattuveettil, Keerthana A1 - Brunner, Nanine A1 - Tiebe, Carlo A1 - Melzer, Michael A1 - Johann, Sergej A1 - Neumann, Patrick P. A1 - Bartholmai, Matthias T1 - Einsatz von Sensortechnologien an einer Wasserstofftankstelle als Beitrag zur digitalen Qualitätsinfrastruktur T1 - Use of sensor technologies at hydrogen test platform as a part of QI Digital N2 - Die Optimierung und Validierung des digitalen Wasserstofftankstellenmanagements mit Sensortechnologien ist das übergeordnete Ziel des Teilprojekts Digitale Qualitätsinfrastruktur mit Sensortechnologien (QIST) am Use Case H2, im Rahmen der digitalen Qualitätsinfrastruktur (QI digital[1]). Hierfür sollen u.a. Sensornetzwerke mit digital-gestützten Auswertungsstrategien intelligent gestaltet werden (Stichwort KI bzw. digitaler Zwilling). Verschiedene, sich ergänzende Sensoren, Systemkomponenten und KI-Methoden stehen als Bausteine intelligenter Sensorsysteme zur Verfügung, mit dem Zweck, die physikalischen und chemischen Parameter an und in Anlagen umfassend und effizient zu überwachen sowie Fehlfunktionen zuverlässig zu detektieren und zu interpretieren, Abbildung 1. Konkrete Arbeitsschritte sind, nach dem Aufbau der Versuchsplattform „Wasserstofftankstelle“, die Instrumentierung von Sensorik und deren digitale Integration in das Tankstellenmanagementsystem sowie die Validierung im Realbetrieb. Die somit erzielten Messergebisse sowie die Messunsicherheiten, Historien und Verfahren werden in digitaler Form aufbereitet, gespeichert und fortlaufend in die KI-basierte Datenauswertung einbezogen, inkl. der Anbindung an die metrologische Rückführungskette. Ziele sind: • Einführung eines neuen messtechnischen Ansatzes und eines digitalen Zwillings für den Anwendungsfall "Wasserstofftankstelle" auf Basis der H2-Sensorik sowie der Zustandsgrößen Druck und Temperatur • Qualitätssicherung durch Applikationen zuverlässiger Gassensorik, Manometer und Thermometer sowie KI-Methoden zur Prozesskontrolle und Detektion von Fehlfunktionen • Nutzung von digitalen Kalibrierscheinen (DCCs) insbesondere für die Messgröße Temperatur zur Realisierung der metrologischen Rückführung in einer digitalen Qualitätsinfrastruktur T2 - Sensorik für die Digitalisierung chemischer Produktionsanlagen CY - Frankfurt a. M., Germany DA - 13.06.2022 KW - QI Digital KW - H2Safety@BAM KW - Wasserstoff KW - Hydrogen KW - Sensorik KW - Digitalisierung KW - Digitalisation PY - 2022 AN - OPUS4-55399 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Moufid, M. A1 - Tiebe, Carlo A1 - El Bari, N. A1 - Bartholmai, Matthias A1 - Bouchikhi, B. T1 - Characterization of Unpleasant Odors in Poultry Houses Using Metal Oxide Semiconductor-Based Gas Sensor Arrays and Pattern Recognition Methods T2 - The 1st International Electronic Conference on Chemical Sensors and Analytical Chemistry) N2 - In this study, the ability of an electronic nose developed to analyze and monitor odor emissions from three poultry farms located in Meknes (Morocco) and Berlin (Germany) was evaluated. Indeed, the potentiality of the electronic nose (e-nose) to differentiate the concentration fractions of hydrogen sulfide, ammonia, and ethanol was investigated. Furthermore, the impact change of relative humidity values (from 15% to 67%) on the responses of the gas sensors was reported and revealed that the effect remained less than 0.6%. Furthermore, the relevant results confirmed that the developed e-nose system was able to perfectly classify and monitor the odorous air of poultry farms. T2 - 1st International Electronic Conference on Chemical Sensors and Analytical Chemistry CY - Online meeting DA - 01.07.2021 KW - Pattern recognition methods KW - Gas sensors KW - Electronic nose KW - poultry odorous air monitoring PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-544005 UR - https://csac2021.sciforum.net/ DO - https://doi.org/10.3390/CSAC2021-10481 VL - 5 IS - 52 SP - 1 EP - 7 PB - MDPI AN - OPUS4-54400 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Moufid, M. A1 - Tiebe, Carlo A1 - El Bari, N. A1 - Bartholmai, Matthias A1 - Bouchikhi, B. T1 - Combining of TD-GC-MS and home developed electronic nose for road traffic air monitoring T2 - 2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS) N2 - In this work, we demonstrate the ability of an electronic nose system based on an array of six-semiconductor gas sensors for outdoor air quality monitoring over a day at a traffic road in downtown of Meknes city (Morocco). The response of the sensor array reaches its maximum in the evening of the investigated day which may due to high vehicular traffic or/and human habits resulting in elevated concentrations of pollutants. Dataset treatment by Principal Component Analysis and Discriminant Function Analysis shows a good discrimination between samples collected at different times of the day. Moreover, Support Vector Machines were used and reached a classification success rate of 97.5 %. Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS) technique was used to validate the developed e-nose system by identifying the composition of the analyzed air samples. The discrimination obtained by e-nose system was in good agreement with the TD-GC-MS results. This study demonstrates the usefulness of TD-GC-MS and e-nose, providing high accuracy in discriminating outdoor air samples collected at different times. This demonstrates the potential of using the e-nose as a rapid, easy to use and inexpensive environmental monitoring system. T2 - 2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS) CY - Sfax, Tunisia DA - 07.06.2021 KW - GC-MS KW - Electronic nose KW - Gas sensors KW - Urban air monitoring PY - 2021 DO - https://doi.org/10.1109/DTS52014.2021.9498110 SP - 1 EP - 6 AN - OPUS4-54401 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Gawlitza, Kornelia A1 - Johann, Sergej A1 - Mansurova, Maria A1 - Kohlhoff, Harald A1 - Tiebe, Carlo A1 - Bell, Jérémy A1 - Bartholmai, Matthias A1 - Rurack, Knut T1 - Semi-automatic Measurement Device for Long-Term Monitoring of Ammonia in Gas Phase T2 - SMSI 2021 Proceedings N2 - In the present paper the development of a semi-automated device for long-term monitoring of gaseous ammonia is described. A sensor material was produced that changes its optical properties in the pres-ence of low concentrations of ammonia in air. The implementation into an electronic device enables precise, simple, economic and fast monitoring of low concentrations of harmful gases, like ammonia, and hence can help to improve the climate monitoring in livestock housing, barns or stables. T2 - SMSI 2021 CY - Online meeting DA - 03.05.2021 KW - Spectroscopy KW - Embedded sensor KW - Environment KW - Air quality PY - 2021 SP - 133 EP - 134 AN - OPUS4-52576 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Johann, Sergej A1 - Tiebe, Carlo A1 - Kohlhoff, Harald A1 - Bartholmai, Matthias T1 - Feasibility Study for Safe Workplaces through automation and digitalization technology with redesigned Smart Sensors and LoRaWAN Monitoring System T2 - SMSI 2021 Proceedings N2 - This project addresses the application of safe and healthy workplaces in offices, chemical laboratories and other workplaces where indoor air quality plays an important role. The LoRaWAN (Long Range Wide Area Network) is used as a communication interface to make sensor data globally accessible. The objectives of the project are to create a sensor node and an online and offline system that collects the data from the sensor nodes and stores it on a local server, in a cloud, and also locally on the node to prevent communication failures. An important point in this project is the development of the sensor nodes and the placement of these in the premises, thus no development work is involved in Building the infrastructure. T2 - SMSI 2021 CY - Online meeting DA - 03.05.2021 KW - Smart sensors KW - Air quality monitoring KW - LoRaWAN KW - VOC KW - Multisensor system PY - 2021 SP - 230 EP - 231 AN - OPUS4-52649 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Moufid, M. A1 - Bouchikhi, B. A1 - Tiebe, Carlo A1 - Bartholmai, Matthias A1 - El Bari, N. T1 - Assessment of outdoor odor emissions from polluted sites using simultaneous thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS), electronic nose in conjunction with advanced multivariate statistical approaches JF - Atmospheric Environment N2 - Poor air quality, particularly in urban areas, causes various diseases and degrades living standards. Air Quality could be affected by emissions of odor, Volatile Organic Compounds (VOCs), and other gases. Therefore, assessment and monitoring of odorous air quality using sensitive, simple, rapid, accurate and portable tools is very important for public health. This study aimed to characterize odor emissions to detect malfunctions in facilities and to prevent air pollution and olfactory nuisance in the environment. A gas chromatographic method, in conjunction with sensorial analysis were performed for odorous air samples analysis collected from neighborhood of Meknes city (Morocco). Advanced multivariate statistical approaches, such as Principal Components Analysis (PCA), Discriminant Function Analysis (DFA), Support Vector Machines (SVMs), and Hierarchical Cluster Analysis (HCA), were used to describe samples similarities. The electronic nose (e-nose) data processing exhibits a satisfactory discrimination between the odorous air samples. Twenty-four VOCs with known molecular formulas were identified with Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS). A validated Partial Least Square (PLS) model foresees good calibration between e-nose measurement and TD-GCMS analysis. The finding indicates that TD-GC–MS approach in conjunction with e-nose unit could be suitable tool for environmental measurement-based odor emissions. KW - Electronic nose KW - TD-GC-MS KW - PLS regression KW - Multivariate analysis KW - Outdoor odor emissions PY - 2021 DO - https://doi.org/10.1016/j.atmosenv.2021.118449 SN - 1352-2310 VL - 256 SP - 118449 PB - Elsevier Ltd. AN - OPUS4-52626 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Moufid, M. A1 - Hofmann, Michael A1 - El Bari, N. A1 - Tiebe, Carlo A1 - Bartholmai, Matthias A1 - Bouchikhi, B. T1 - Wastewater monitoring by means of e-nose, VE-tongue, TD-GC-MS, and SPME-GC-MS JF - Talanta N2 - The presence of wastewater and air pollution has become an important risk factor for citizens, not only in terms of problems related to health risks, but also because of its negative impact on the country's image. For this reason, malodorous emission monitoring and control techniques are in high demand in urban areas and industries. The aim of this work is first to build an electronic nose (e-nose) and a Voltammetric Electronic tongue (VE-tongue) in order to study their ability to discriminate between polluted and clean environmental samples. Secondly, Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS), and Solid Phase Micro Extraction-Gas Chromatography–Mass Spectrometry (SPME-GC-MS) are utilized to explain this discrimination by identifying specific compounds from these samples. Indeed, the e-nose, consisted of metal oxide semiconductor gas sensors, is used for the assessment of the studied odorous air and headspace samples from water and wastewater sites. Moreover, the VE-tongue, based on metal electrodes, is utilized to determine the patterns of the sensor array responses, which serve as fingerprints profiles of the analyzed liquid samples. Chemometric tools, such as Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Support Vector Machines (SVMs) are operated for the processing of data from the e-nose and the VE-tongue. By using the both systems, the analyses of headspace and liquid samples from the seven sites allow better discrimination. To explain the cause of the obtained discrimination, TD-GC-MS and SPME-GC-MS analyses are well performed to identify compounds related sites. According to these outcomes, the proposed e-nose and VE-tongue are proved to be rapid and valuable tools for analysis of environmental polluted matrices. KW - Wastewater KW - Electronic nose KW - Voltammetric electronic tongue KW - Thermal desorption-gas chromatography-mass spectrometry KW - Solid phase micro extraction-gas chromatography–mass spectrometry PY - 2021 DO - https://doi.org/10.1016/j.talanta.2020.121450 VL - 221 SP - 121450 PB - Elsevier B.V. AN - OPUS4-51099 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -