TY - CONF A1 - Winkler, Nicolas P. A1 - Neumann, Patrick P. A1 - Schaffernicht, E. A1 - Lilienthal, A. J. T1 - Heterogeneous Sensor Networks: Challenges and Insights from an Industrial Scenario N2 - Monitoring airborne pollutants is critical for occupational health, particularly in industrial environments where workers are exposed to hazardous emissions. Traditional measurements are typically limited to single-day campaigns, resulting in extremely sparse temporal data. Low-cost sensor networks offer a way to increase spatial and temporal resolution but are limited by issues of accuracy and reliability. To address this, we present a wireless heterogeneous sensor network that integrates low-cost stationary nodes with high-quality sensors on mobile platforms, including ground and aerial robots. We deploy this system in a hot rolling mill facility and evaluate its performance under real-world conditions. Field experiments reveal dynamic pollutant patterns, such as altitude-dependent PM2.5 gradients and temperature fluctuations. By introducing synchronized “rendezvous” events between mobile and stationary nodes, we demonstrate correlation capabilities of sensors. Our spatiotemporal analysis shows that, despite limitations of mobile sensing, strategically combining heterogeneous data sources enables capturing pollutant dynamics in complex industrial settings. T2 - IEEE SENSORS 2025 CY - Vancouver, BC, Kanada DA - 19.10.2025 KW - Environmental monitoring KW - Sensor data fusion KW - Sensor system networks KW - Mobile robotics PY - 2025 SN - 979-8-3315-4467-6 SP - 1 EP - 4 PB - IEEE CY - Piscataway, NJ, USA AN - OPUS4-64501 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Neumann, Patrick P. A1 - Asadi, S. A1 - Lilienthal, A.J. A1 - Bartholmai, Matthias A1 - Schiller, J.H. T1 - Autonomous gas-sensitive microdrone - wind vector estimation and gas distribution mapping N2 - This article presents the development and validation of an autonomous, gas sensitive microdrone that is capable of estimating the wind vector in real time using only the onboard control unit of the microdrone and performing gas distribution mapping (DM). Two different sampling approaches are suggested to address this problem. On the one hand, a predefined trajectory is used to explore the target area with the microdrone in a real-world gas DM experiment. As an alternative sampling approach, we introduce an adaptive strategy that suggests next sampling points based on an artificial potential field (APF). Initial results in real-world experiments demonstrate the capability of the proposed adaptive sampling strategy for gas DM and its use for gas source localization. KW - Anemometric sensor KW - Autonomous micro UAV KW - Chemical sensing KW - Gas distribution modelling KW - Gas source localization KW - Gas sensors KW - Mobile sensing system KW - Quadrocopter KW - Sensor planning KW - Artificial potential field PY - 2012 DO - https://doi.org/10.1109/MRA.2012.2184671 SN - 1070-9932 VL - 19 IS - 1 SP - 50 EP - 61 PB - IEEE CY - New York, NY, USA AN - OPUS4-25773 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hüllmann, Dino A1 - Neumann, Patrick P. A1 - Scheuschner, Nils A1 - Bartholmai, Matthias A1 - Lilienthal, A.J. T1 - Experimental Validation of the Cone-Shaped Remote Gas Sensor Model N2 - Remote gas sensors mounted on mobile robots enable the mapping of gas distributions in large or hardly accessible areas. A challenging task, however, is the generation of threedimensional distribution maps from these gas measurements. Suitable reconstruction algorithms can be adapted, for instance, from the field of computed tomography (CT), but both their performance and strategies for selecting optimal measuring poses must be evaluated. For this purpose simulations are used, since, in contrast to field tests, they allow repeatable conditions. Although several simulation tools exist, they lack realistic models of remote gas sensors. Recently, we introduced a model for a Tunable Diode Laser Absorption Spectroscopy (TDLAS) gas sensor taking into account the conical shape of its laser beam. However, the novel model has not yet been validated with experiments. In this paper, we compare our model with a real sensor device and show that the assumptions made hold. T2 - IEEE Sensors 2019 CY - Montreal, Canada DA - 27.10.2019 KW - Remote gas sensor model KW - TDLAS KW - Gas dispersion simulation PY - 2019 SN - 978-1-7281-1634-1 SP - 104 EP - 107 PB - IEEE AN - OPUS4-49548 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Winkler, Nicolas P. A1 - Lilienthal, A. J. A1 - Neumann, Patrick P. ED - Zemčík, R. ED - Krystek, J. T1 - Boosting a Low-Cost Sensor Network with Mobile High-Quality Sensors 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. Recent developments in sensor technology enable cost-efficient gas monitoring in real-time for long-term intervals. This knowledge of contaminant distribution inside the industrial environment would provide means for better and more economic control of air impurities, e.g., the possibility to regulate the workspace’s ventilation exhaust locations, can reduce the concentration of airborne contaminants by 50%. This paper describes a concept proposed in the project “Robot-assisted Environmental Monitoring for Air Quality Assessment in Industrial Scenarios“ (RASEM). RASEM aims to bring together the benefits of both – low- and high-cost – measuring technologies: A stationary network of low-cost sensors shall be augmented by mobile units carrying high-quality sensors. Additionally, RASEM will develop procedures and algorithms to map the distribution of gases and particles in industrial environments. 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 SP - 61 EP - 62 CY - Plzeň AN - OPUS4-49630 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hüllmann, Dino A1 - Neumann, Patrick P. A1 - Monroy, J. A1 - Lilienthal, A. J. T1 - A realistic remote gas sensor model for three-dimensional olfaction simulations N2 - Remote gas sensors like those based on the Tunable Diode Laser Absorption Spectroscopy (TDLAS) enable mobile robots to scan huge areas for gas concentrations in reasonable time and are therefore well suited for tasks such as gas emission surveillance and environmental monitoring. A further advantage of remote sensors is that the gas distribution is not disturbed by the sensing platform itself if the measurements are carried out from a sufficient distance, which is particularly interesting when a rotary-wing platform is used. Since there is no possibility to obtain ground truth measurements of gas distributions, simulations are used to develop and evaluate suitable olfaction algorithms. For this purpose several models of in-situ gas sensors have been developed, but models of remote gas sensors are missing. In this paper we present two novel 3D ray-tracer-based TDLAS sensor models. While the first model simplifies the laser beam as a line, the second model takes the conical shape of the beam into account. Using a simulated gas plume, we compare the line model with the cone model in terms of accuracy and computational cost and show that the results generated by the cone model can differ significantly from those of the line model. T2 - 2019 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) CY - Fukuoka, Japan DA - 26.05.2019 KW - Remote gas sensor KW - Gas detector KW - TDLAS KW - Sensor modelling PY - 2019 SN - 978-1-5386-8327-9 SN - 978-1-5386-8328-6 DO - https://doi.org/10.1109/ISOEN.2019.8823330 SP - 1 EP - 3 PB - IEEE AN - OPUS4-48919 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Neumann, Patrick P. A1 - Kohlhoff, Harald A1 - Hüllmann, Dino A1 - Krentel, Daniel A1 - Kluge, Martin A1 - Dzierliński, M. A1 - Lilienthal, A. J. A1 - Bartholmai, Matthias T1 - Aerial-based gas tomography – from single beams to complex gas distributions N2 - In this paper, we present and validate the concept of an autonomous aerial robot to reconstruct tomographic 2D slices of gas plumes in outdoor environments. Our platform, the so-called Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS), combines a lightweight Tunable Diode Laser Absorption Spectroscopy (TDLAS) gas sensor with a 3-axis aerial stabilization gimbal for aiming at a versatile octocopter. While the TDLAS sensor provides integral gas concentration measurements, it does not measure the distance traveled by the laser diode’s beam nor the distribution of gas along the optical path. Thus, we complement the set-up with a laser rangefinder and apply principles of Computed Tomography (CT) to create a model of the spatial gas distribution from a set of integral concentration measurements. To allow for a fundamental ground truth evaluation of the applied gas tomography algorithm, we set up a unique outdoor test environment based on two 3D ultrasonic anemometers and a distributed array of 10 infrared gas transmitters. We present results showing its performance characteristics and 2D plume reconstruction capabilities under realistic conditions. The proposed system can be deployed in scenarios that cannot be addressed by currently available robots and thus constitutes a significant step forward for the field of Mobile Robot Olfaction (MRO). KW - Aerial robot olfaction KW - Mobile robot olfaction KW - Gas tomography KW - TDLAS KW - Plume PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-487843 DO - https://doi.org/10.1080/22797254.2019.1640078 SP - 1 EP - 16 PB - Taylor & Francis CY - London AN - OPUS4-48784 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hüllmann, Dino A1 - Neumann, Patrick P. A1 - Lilienthal, A. J. T1 - Gas Dispersion Fluid Mechanics Simulation for Large Outdoor Environments N2 - The development of algorithms for mapping gas distributions and localising gas sources is a challenging task, because gas dispersion is a highly dynamic process and it is impossible to capture ground truth data. Fluid-mechanical simulations are a suitable way to support the development of these algorithms. Several tools for gas dispersion simulation have been developed, but they are not suitable for simulations of large outdoor environments. In this paper, we present a concept of how an existing simulator can be extended to handle both indoor and large outdoor scenarios. T2 - 36th Danubia Adria Symposium on Advances in Experimental Mechanics CY - Pilsen, Czech Republic DA - 24.09.2019 KW - Gas dispersion simulation KW - CFD KW - Gas tomography PY - 2019 SN - 978-80-261-0876-4 SP - 49 EP - 50 CY - Pilsen, Czech Republic AN - OPUS4-49224 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -