TY - CONF A1 - Neumann, Patrick P. A1 - Winkler, Nicolas P. A1 - Nerger, Tino A1 - Lohrke, Heiko A1 - Stanisavljevi, Mila T1 - DLR Research Seminar - ARO Lab@BAM – Current Research Topics N2 - This seminar presents the key research activities of ARO Lab@BAM, focusing on five main areas: • Learning-based Gas Distribution Mapping utilizes machine learning to accurately model and predict spatial gas concentrations, enhancing environmental monitoring and safety. • Mimose-A develops autonomous systems using artificial intelligence to enable the early detection of leaks in industrial environments. • AGATO (Gastomography) introduces a novel robotic system for high-resolution gas distribution mapping. • Passive Smart Dust detects chemically hazardous substances using drones equipped to distribute and detect particles carrying selective dyes, enabling rapid and reliable monitoring without complex components. • HyAirLogic Lab advances hydrogen (H₂) research by testing the entire value chain in various Berlin-Brandenburg quarters, addressing technological challenges, public acceptance, and sustainable energy solutions for H₂-cargo drones. T2 - DLR Research Seminar CY - Weßling, Germany DA - 04.11.2024 KW - Aerial robot KW - Learning Based Gas Distribution Mapping KW - Mobile Robotic Olfaction KW - Aerial-based Gas Tomography KW - Passive Smart Dust PY - 2024 AN - OPUS4-61611 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 - Lohrke, Heiko A1 - Bartholmai, Matthias T1 - Robotic Olfaction in Action: Field Applications and Results from Current Research N2 - In recent decades, robotics, particularly in environmental monitoring, has made significant advances. Robots of various forms and sizes have become essential tools for data collection in environmental research. Mobile Robot Olfaction (MRO) involves mobile robots equipped with gas sensors and requires the integration of multiple disciplines, including signal processing, machine perception, autonomous navigation, and pattern recognition. Common applications of MRO include mapping gas distributions, locating and detecting gas sources, and tracking gas plumes. Aerial Robot Olfaction (ARO) is a specialized branch of MRO that adapts these concepts to aerial robots, addressing the challenges of airborne gas sensing. This presentation highlights recent developments and results from ongoing research projects in MRO and ARO, with a focus on real-world deployment scenarios and the challenges encountered in practice. T2 - Drohnen in der Zerstörungsfreien Prüfung CY - Magdeburg, Germany DA - 26.11.2025 KW - Ground and Aerial robots KW - Gas distribution mapping KW - Gas source localization KW - Gas Tomography KW - Mobile Robotic Olfaction PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-648928 UR - https://www.ndt.net SP - 1 EP - 15 PB - DGZfP AN - OPUS4-64892 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Nerger, Tino A1 - Neumann, Patrick P. A1 - Weller, Michael G. T1 - A New Approach: Passive Smart Dust for Detection of Hazardous Substances N2 - Remote sensing of hazardous substances is a key task that can be achieved with the help of remotely operated platforms equipped with specific sensors. A huge variety of methods and used vehicles have been developed for different purposes in recent years. The term smart dust refers to a science fiction novel and develop shortly after into a research proposal at UC Berkley funded by DARPA. Subsequently, the topic gained attraction but was overall considered as to complex for the technologies available at that time. In the launched passive smart dust project, we shift to a simple “chemical intelligent” passive sensor particle on the ground combined a read-out active sensor attached to an Unmanned Aerial Vehicle (UAV). The reactive particle surface can be preadjusted in the lab for exact desired properties regarding certain reactions to hazardous substances. Moreover, the aimed interaction with the active sensor can be modified. Planed applications allow for different materials e.g., for short time measurement, being ecologically degradable, or weather stable for long time monitoring. T2 - 38th Danubia-Adria Symposium on Advances in Experimental Mechanics CY - Poros, Greece DA - 20.09.2022 KW - Smart Dust KW - Drone KW - Remote Detection KW - Hazardous substances PY - 2022 SP - 1 EP - 2 CY - Athens, Greece AN - OPUS4-55925 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - INPR A1 - Nerger, Tino A1 - Neumann, Patrick P. A1 - Weller, Michael G. T1 - Drone-Based Localization of Hazardous Chemicals by Passive Smart Dust N2 - The distribution of tiny sensors over a specific area was first proposed in the late 1990s as a concept known as Smart Dust. Several efforts focused primarily on computing and networking capabilities but quickly ran into problems related to power supply, cost, data transmission, and environmental pollution. To overcome these limitations, we propose using paper-based (confetti-like) chemosensors that exploit the inherent selectivity of chemical reagents, such as colorimetric indicators. In this work, cheap and biodegradable passive sensors made from cellulose could successfully indicate the presence of hazardous chemicals, e.g., strong acids, by a significant color change. A conventional color digital camera attached to a drone could easily detect this from a safe distance. The collected data was processed to define the hazardous area. Our work presents a combination of the smart dust concept, chemosensing, paper-based sensor technology, and low-cost drones for flexible, sensitive, economical, and rapid detection of hazardous chemicals in high-risk scenarios. N2 - Die Verteilung winziger Sensoren über ein bestimmtes Gebiet wurde erstmals Ende der 1990er Jahre als Konzept namens „Smart Dust“ vorgeschlagen. Mehrere Bemühungen konzentrierten sich hauptsächlich auf Rechen- und Netzwerkfähigkeiten, stießen jedoch schnell auf Probleme im Zusammenhang mit der Stromversorgung, den Kosten, der Datenübertragung und der Umweltverschmutzung. Um diese Einschränkungen zu überwinden, schlagen wir die Verwendung von papierbasierten (konfettiartigen) Chemosensoren vor, die die inhärente Selektivität chemischer Reagenzien, wie z. B. kolorimetrischer Indikatoren, nutzen. In dieser Arbeit konnten günstige und biologisch abbaubare passive Sensoren aus Zellulose erfolgreich das Vorhandensein gefährlicher Chemikalien, z.B. starker Säuren, durch eine deutliche Farbänderung anzeigen. Eine herkömmliche Farb-Digitalkamera, die an einer Drohne befestigt ist, konnte dies aus sicherer Entfernung leicht erkennen. Die gesammelten Daten wurden verarbeitet, um den Gefahrenbereich zu abzugrenzen. Unsere Arbeit stellt eine Kombination aus dem Smart-Dust-Konzept, Chemosensorik, papierbasierter Sensortechnologie und kostengünstigen Drohnen für eine flexible, empfindliche, wirtschaftliche und schnelle Erkennung gefährlicher Chemikalien in Hochrisikoszenarien dar. KW - Confetti KW - Remote sensing KW - Drones KW - UAV KW - Optical detection KW - Chemosensor KW - pH indicator KW - Paper-based sensors KW - Harmful chemicals KW - Chemical desaster PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-621284 DO - https://doi.org/10.20944/preprints202408.0030.v1 SP - 1 EP - 17 PB - MDPI CY - Basle, Switzerland AN - OPUS4-62128 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Nerger, Tino A1 - Neumann, Patrick P. A1 - Weller, Michael G. T1 - Passive Smart Dust For Detection Of Hazardous Substances N2 - High demand for remote sensing of hazardous substances. Possible solution: Use of distributed, low cost, and environmentally safe particles as passive sensors that can be read out remotely Chemical intelligence on the particle surface can be easily modified Particles enable optically quantifiable response and inference of target substances (also no maintenance or power supply required T2 - 38th Danubia-Adria Symposium on Advances in Experimental Mechanics CY - Poros, Greece DA - 20.09.2022 KW - Smart Dust KW - Drone KW - Remote Detection KW - Colorchanging Particles PY - 2022 AN - OPUS4-56025 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Nerger, Tino A1 - Neumann, Patrick P. A1 - Weller, Michael G. T1 - Drone-based Localization of Hazardous Chemicals by Passive Smart Dust N2 - We introduce a passive smart dust concept as a novel solution for environmental monitoring. Utilizing chemical reagents like colorimetric indicators and other chemosensors, these particles detect varying environmental conditions. We developed paper-based sensors that are both cost-effective and eco-friendly. In practical tests, these sensors, dispersed over a designated area, successfully identified hazardous substances by changing their color when exposed to acids or bases. This color change was remotely detectable using a drone-mounted color camera. The data thus obtained was processed through specialized software, accurately pinpointing areas of contamination. This method proves the efficacy and scalability of passive smart dust technology for real-time, environmentally sustainable remote sensing of hazardous materials T2 - 2024 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) CY - Grapevine, Texas, USA DA - 12.05.2024 KW - Indicator KW - Passive Smart Dust KW - Colorimetric Sensor KW - Drone KW - Cellulose KW - Environmental Monitoring KW - Confetti KW - Hazard Detection PY - 2024 SN - 979-8-3503-7053-9 VL - 1 SP - 1 EP - 3 PB - IEEE CY - Piscataway, NJ 08855-1331 USA AN - OPUS4-60176 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Nerger, Tino A1 - Neumann, Patrick P. A1 - Weller, Michael G. T1 - Passive Smart Dust a versatile low-cost sensor platform N2 - Coated cellulose particles as colourimetric passive sensors that are detected by the optical camera system of a drone. In this way, hazardous substances, e.g. acids, can be detected from a safe distance in a cost-effective and environmentally friendly way. N2 - Beschichtete Zellulose Partikel als kolorimetrische passive Sensoren, die mittels optische Kamerasystem einer Drohne erfasst werden. Somit können Gefahrenstoffe, in ersten Versuchen zB Säuren aus sicherer Entfernung, kostengünstig und umweltverträglich detektiert werden. T2 - SMSI 2023 Sensor and Measurement Science International CY - Nuremberg, Germany DA - 08.05.2023 KW - Passive Smart Dust KW - Drone KW - Colorimetric sensor particles KW - Remote detection PY - 2023 DO - https://doi.org/10.5162/SMSI2023/C5.3 SP - 1 EP - 2 AN - OPUS4-57527 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Nerger, Tino T1 - Passive Smart Dust: A versatile low-cost sensor platform N2 - Beschichtete Zellulose Partikel als kolorimetrische passive Sensoren, die mittels optische Kamerasystem einer Drohne erfasst werden. Somit können Gefahrenstoffe, in ersten Versuchen z. B. Säuren aus sicherer Entfernung, kostengünstig und umweltverträglich detektiert werden. T2 - SMSI 2023 Sensor and Measurement Science International CY - Nuremberg, Germany DA - 08.05.2023 KW - Passive Smart Dust KW - Drone KW - Colorimetric sensor particles PY - 2023 AN - OPUS4-57526 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Nerger, Tino T1 - Passive Smart Dust zur Erkennung gefährlicher Stoffe N2 - Einsatz/Verteilung kostengünstiger und umweltfreundlicher Partikel als passive Sensoren und optische Detektion per Kamerasystem. Die einfache Modifikation chemischen Farbstoffe auf der Partikeloberfläche liefert eine optisch quantifizierbare Reaktion und Rückschlüsse auf die Zielsubstanzen. T2 - Lange Nacht der Wissenschaften @ BAM 2023 CY - Berlin, Germany DA - 17.06.2023 KW - Passive Smart Dust KW - Drohne KW - Kolorimetrische Sensoren KW - Cellulose PY - 2023 AN - OPUS4-58140 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Nerger, Tino T1 - Passive Smart Dust Localization of Hazardous Chemicals N2 - Use/distribution of cost-effective and biocompatible pieces of cellulose paper as passive optical chemosensors and readout by the camera system. Modification of the paper surface using various chemically sensitive dyes (indicators) provides an optically detectable reaction and conclusions about the target substances and precise location. T2 - 2024 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) CY - Grapevine, Texas, USA DA - 12.05.2024 KW - Indicator KW - Passive Smart Dust KW - Drone KW - Colorimetric Sensor KW - Cellulose KW - Confetti PY - 2024 AN - OPUS4-60175 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Sauter, O. A1 - Neumann, Patrick P. A1 - Nerger, Tino A1 - Weller, Michael G. ED - Heß, M. T1 - Aus sicherer Entfernung BT - das Magazin für die Gefahrgut-Logistik N2 - Da chemische Gefahrstoffe im Boden eine ernsthafte Bedrohung für Leben und Gesundheit darstellen, das Grundwasser kontaminieren und langfristige Umweltschäden verursachen können, ist ihre frühzeitige Erkennung von großer Bedeutung. Um solche Gefahrstoffe aus sicherer Entfernung detektieren zu können, wurde bei der Bundesanstalt für Materialforschung und -prüfung (BAM) im Rahmen eines Forschungsvorhabens seit Anfang 2022 an einem neuen Ansatz zur Erkennung und Überwachung chemischer Gefahrstoffe gearbeitet. KW - Cellulose KW - Drohne KW - Kolorimetrische Sensoren KW - Passive Smart Dust PY - 2025 SN - 0016-5808 VL - 2025 IS - 8 SP - 26 EP - 28 PB - ecomed-Storck GmbH, Storck Verlag Hamburg CY - Hamburg AN - OPUS4-64109 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Nerger, Tino T1 - Passive Smart Dust zur Lokalisierung von Gefahrstoffen N2 - Durch einen bestehenden hohen Bedarf an der Fernerkundung gefährlicher Substanzen bieten kostengünstige, biokompatible Cellulose-Papierstücke eine effektive Lösung. Sie dienen als passive optische Chemosensoren und können per Kamerasystem ausgelesen werden. Die Modifikation mit chemisch sensiblen Farbstoffen ermöglicht optisch detektierbare Reaktionen auf Zielsubstanzen. Autonomes Abfliegen großer Gebiete und KI-gestützte Auswertungen mit anpassbaren Gefahrenklassen eröffnen ein breites Einsatzspektrum. Bei Unfällen mit gefährlichen Stoffen kann so eine automatisierte Gefahrenerkennung inklusive Kartierung und exakter Positionsanzeige des kontaminierten Bereichs erfolgen, ohne dass sich Einsatzkräfte riskant nähern müssen. T2 - BMBF-Innovationsforum „Zivile Sicherheit“ CY - Berlin, Germany DA - 07.05.2024 KW - Kolorimetrische Sensoren KW - Passive Smart Dust KW - Drohne KW - Cellulose PY - 2024 AN - OPUS4-61415 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Nerger, Tino A1 - Neumann, Patrick P. A1 - Weller, Michael G. T1 - Drone-Based Localization of Hazardous Chemicals by Passive Smart Dust N2 - The distribution of tiny sensors over a specific area was first proposed in the late 1990s as a concept known as smart dust. Several efforts focused primarily on computing and networking capabilities, but quickly ran into problems related to power supply, cost, data transmission, and environmental pollution. To overcome these limitations, we propose using paper-based (confetti-like) chemosensors that exploit the inherent selectivity of chemical reagents, such as colorimetric indicators. In this work, cheap and biodegradable passive sensors made from cellulose could successfully indicate the presence of hazardous chemicals, e.g., strong acids, by a significant color change. A conventional color digital camera attached to a drone could easily detect this from a safe distance. The collected data were processed to define the hazardous area. Our work presents a combination of the smart dust concept, chemosensing, paper-based sensor technology, and low-cost drones for flexible, sensitive, economical, and rapid detection of hazardous chemicals in high-risk scenarios. KW - Cellulose KW - Passive Smart Dust KW - Drohne KW - Kolorimetrische Sensoren PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-614641 DO - https://doi.org/10.3390/s24196195 VL - 24 IS - 19 SP - 1 EP - 16 PB - MDPI AN - OPUS4-61464 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -