TY - CONF A1 - Sarif, Raduan T1 - Digital twin for hydrogen refueling stations: An analytical study for safe and efficient operations N2 - This analytical overview is the initial study in developing the digital sensors twin for the hydrogen refueling station. The research includes a comprehensive analysis of the current literature, refueling protocol, standards, mathematical model, simulation model, and trends in digital twins and H2 technologies. Furthermore, this study has explored the various HRS attributes, such as leakage, temperature, pressure, and hydrogen flow, and identified different use cases of the hydrogen fuel station to build a digital sensor twin. Various real gas equations, such as the Van der Waals and Able-Noble equation of state (EOS), are applied to analyze the key factors and parameters affecting hydrogen and the MATLAB simulation model to validate the key elements and parameters. This study also focuses on identifying and addressing research gaps in hydrogen technology, contributing to advancing hydrogen infrastructure, and supporting the global transition to cleaner energy solutions. T2 - 10. Fachsymposium des Vereins HybridSensorNet (HSN), KIT CY - Eggenstein-Leopoldshafen, Germany DA - 08.11.2023 KW - Sensor network KW - H2Safety@BAM KW - SensRef KW - Trustworthy hydrogen KW - Digital twin KW - Data analytics PY - 2023 AN - OPUS4-59034 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Winkler, Nicolas P. A1 - Johann, Sergej A1 - Kohlhoff, Harald A1 - Neumann, Patrick P. T1 - Revisiting Environmental Sensing Nodes: Lessons Learned and Way Forward N2 - Setting up sensors for the purpose of environmental monitoring should be a matter of days, but often drags over weeks or even months, preventing scientists from doing real research. Additionally, the newly developed hardware and software solutions are often reinventing existing wheels. In this short paper, we revisit the design of our environmental sensing node that has been monitoring industrial areas over a span of two years. We share our findings and lessons learned. Based on this, we outline how a new generation of sensing node(s) can look like. T2 - SMSI 2023 Conference Sensor and Measurement Science International CY - Nuremberg, Germany DA - 08.05.2023 KW - Sensing node KW - Sensor network KW - Environmental monitoring KW - Low-cost KW - LoRaWAN PY - 2023 SN - 978-3-9819376-8-8 U6 - https://doi.org/10.5162/SMSI2023/C5.1 SP - 173 EP - 174 PB - AMA Service GmbH CY - Wunstorf AN - OPUS4-57454 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Winkler, Nicolas P. A1 - Johann, Sergej A1 - Kohlhoff, Harald A1 - Neumann, Patrick P. T1 - Revisiting Environmental Sensing Nodes: Lessons Learned and Way Forward N2 - Setting up sensors for the purpose of environmental monitoring should be a matter of days, but often drags over weeks or even months, preventing scientists from doing real research. Additionally, the newly developed hardware and software solutions are often reinventing existing wheels. In this short paper, we revisit the design of our environmental sensing node that has been monitoring industrial areas over a span of two years. We share our findings and lessons learned. Based on this, we outline how a new generation of sensing node(s) can look like. T2 - SMSI 2023 Conference Sensor and Measurement Science International CY - Nuremberg, Germany DA - 08.05.2023 KW - Sensing node KW - Sensor network KW - Environmental monitoring KW - Low-cost KW - LoRaWAN PY - 2023 AN - OPUS4-57455 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Neumann, Patrick P. A1 - Winkler, Nicolas P. A1 - Nerger, Tino A1 - Weller, Michael G. A1 - Otremba, Frank A1 - Werner, Jan A1 - Schugardt, Jan T1 - Capabilities of using mobile platforms for monitoring hazard scenarios by the example of the RASEM project N2 - This presentation shows the capabilities of mobile platforms for monitoring hazard scenarios. As an example the RASEM project is presented. Furthermore two ideas for future work are shown, namely, Aerial-based Gas Tomography and Passive Smart Dust. T2 - Climate Change @ Fire Science Workshop CY - Berlin, Germany DA - 10.11.2022 KW - RASEM KW - Dust sensor KW - Low-cost KW - Sensor network KW - Passive Smart Dust KW - Gas Tomography PY - 2022 AN - OPUS4-56296 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Neumann, Patrick P. A1 - Kohlhoff, Harald A1 - Johann, Sergej A1 - Erdmann, Jessica A1 - Winkler, Nicolas P. ED - Kourkoulis, S. K. T1 - The RASEM System: A Technical Overview N2 - Occupational health is an important topic, especially in industry, where workers are exposed to airborne by-products (e.g., dust particles and gases). Therefore, continuous monitoring of the air quality in industrial environments is crucial to meet safety standards. For practical and economic reasons, high-quality, costly measurements are currently only carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. The project “Robot-assisted Environmental Monitoring for Air Quality Assessment in Industrial Scenarios” (RASEM) addresses this issue by bringing together the benefits of both – low- and high-cost – measuring technologies enabling costefficient long-term air quality monitoring in realtime: A stationary network of low-cost sensors that is augmented by mobile units carrying high-quality sensors. By mapping the distribution of gases and particles in industrial environments with the proposed RASEM system, measures can be identified to improve on-site working conditions much faster than using traditional methods. In this paper, we detail the technical aspects of RASEM and introduce the mobile platforms used. T2 - 38th Danubia-Adria Symposium on Advances in Experimental Mechanics CY - Poros, Greece DA - 20.09.2022 KW - RASEM KW - Dust sensor KW - Low-cost KW - Sensor network KW - Ground Robot KW - Aerial Robot PY - 2022 SP - 1 EP - 2 CY - Athens, Greece AN - OPUS4-55915 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Neumann, Patrick P. A1 - Kohlhoff, Harald A1 - Johann, Sergej A1 - Erdmann, Jessica A1 - Winkler, Nicolas P. T1 - The RASEM System: A Technical Overview N2 - Occupational health is an important topic, especially in industry, where workers are exposed to airborne by-products (e.g., dust particles and gases). Therefore, continuous monitoring of the air quality in industrial environments is crucial to meet safety standards. For practical and economic reasons, high-quality, costly measurements are currently only carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. The project “Robot-assisted Environmental Monitoring for Air Quality Assessment in Industrial Scenarios” (RASEM) addresses this issue by bringing together the benefits of both – low- and high-cost – measuring technologies enabling cost-efficient long-term air quality monitoring in realtime: A stationary network of low-cost sensors that is augmented by mobile units carrying high-quality sensors. By mapping the distribution of gases and particles in industrial environments with the proposed RASEM system, measures can be identified to improve on-site working conditions much faster than using traditional methods. In this presentation, we detail the technical aspects of RASEM and introduce the mobile platforms used. T2 - 38th Danubia-Adria Symposium on Advances in Experimental Mechanics CY - Poros, Greece DA - 20.09.2022 KW - RASEM KW - Dust sensor KW - Low-cost KW - Sensor network KW - Ground Robot KW - Aerial Robot PY - 2022 AN - OPUS4-55916 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Winkler, Nicolas P. A1 - Neumann, Patrick P. A1 - Schaffernicht, E. A1 - Lilienthal, A. J. A1 - Poikkimäki, M. A1 - Kangas, A. A1 - Säämänen, A. ED - Kourkoulis, S. K. T1 - Gather Dust and Get Dusted: Long-Term Drift and Cleaning of Sharp GP2Y1010AU0F Dust Sensor in a Steel Factory N2 - The Sharp GP2Y1010AU0F is a widely used low-cost dust sensor, but despite its popularity, the manufacturer provides little information on the sensor. We installed 16 sensing nodes with Sharp dust sensors in a hot rolling mill of a steel factory. Our analysis shows a clear correlation between sensor drift and accumulated production of the steel factory. An eye should be kept on the long-term drift of the sensors to prevent early saturation. Two of 16 sensors experienced full saturation, each after around eight and ten months of operation. T2 - 38th Danubia-Adria Symposium on Advances in Experimental Mechanics CY - Poros, Greece DA - 20.09.2022 KW - Low-cost KW - Dust sensor KW - Sensor network KW - Sensor drift PY - 2022 SP - 1 EP - 2 CY - Athens, Greece AN - OPUS4-55909 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Winkler, Nicolas P. A1 - Neumann, Patrick P. A1 - Schaffernicht, E. A1 - Lilienthal, A. J. A1 - Poikkimäki, M. A1 - Kangas, A. A1 - Säämänen, A. T1 - Gather Dust and Get Dusted: Long-Term Drift and Cleaning of Sharp GP2Y1010AU0F Dust Sensor in a Steel Factory N2 - The Sharp GP2Y1010AU0F is a widely used low-cost dust sensor, but despite its popularity, the manufacturer provides little information on the sensor. We installed 16 sensing nodes with Sharp dust sensors in a hot rolling mill of a steel factory. Our analysis shows a clear correlation between sensor drift and accumulated production of the steel factory. An eye should be kept on the long-term drift of the sensors to prevent early saturation. Two of 16 sensors experienced full saturation, each after around eight and ten months of operation. T2 - 38th Danubia-Adria Symposium on Advances in Experimental Mechanics CY - Poros, Greece DA - 20.09.2022 KW - Low-cost KW - Sensor network KW - Dust sensor KW - Sensor drift PY - 2022 AN - OPUS4-55908 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Winkler, Nicolas P. A1 - Neumann, Patrick P. A1 - Kohlhoff, Harald A1 - Erdmann, Jessica A1 - Schaffernicht, Erik A1 - Lilienthal, Achim J. T1 - Development of a Low-Cost Sensing Node with Active Ventilation Fan for Air Pollution Monitoring N2 - A fully designed low-cost sensing node for air pollution monitoring and calibration results for several low-cost gas sensors are presented. As the state of the art is lacking information on the importance of an active ventilation system, the effect of an active fan is compared to the passive ventilation of a lamellar structured casing. Measurements obtained in an urban outdoor environment show that readings of the low-cost dust sensor (Sharp GP2Y1010AU0F) are distorted by the active ventilation system. While this behavior requires further research, a correlation with temperature and humidity inside the node shown. T2 - SMSI 2021 Conference: Sensor and Measurement Science International CY - Online meeting DA - 03.05.2021 KW - Wireless sensing node KW - Air pollution KW - Sensor network KW - Environmental monitoring PY - 2021 U6 - https://doi.org/10.5162/SMSI2021/D3.5 VL - 2021 SP - 260 EP - 261 AN - OPUS4-52607 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Winkler, Nicolas P. A1 - Neumann, Patrick P. A1 - Kohlhoff, Harald A1 - Bartholmai, Matthias A1 - Lilienthal, A. J. T1 - Boosting a Low-Cost Sensor Network with Mobile High-Quality Sensors N2 - The Motivation of RASEM (Robot-assisted Environmental Monitoring): Monitoring of the air quality in industrial environments is inevitable to meet safety Standards. Because of economic and practical reasons, measurements are carried out sparsely in terms of time and space. Newest developments on the field of low cost sensor technology enable cost efficient long term monitoring of gases and dust T2 - 36th Danubia-Adria Symposium on Advances in Experimental Mechanics CY - Pilsen, Czech Republic DA - 24.09.2019 KW - RASEM KW - Sensor network KW - Low-cost KW - Occupational health KW - Mobile Robot Olfaction PY - 2019 AN - OPUS4-49632 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -