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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.
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.
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.
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.
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
Leaking methane (CH4) from infrastructures, such as pipelines and landfills, is critical for the environment but can also pose a safety risk. To enable a fast detection and localization of these kind of leaks, we developed a novel robotic platform for aerial remote gas sensing. Spectroscopic measurement methods for remote sensing of selected gases lend themselves for use on mini-copters, which offer a number of advantages for inspection and surveillance over traditional methods. No direct contact with the target gas is needed and thus the influence of the aerial platform on the measured gas plume can be kept to a minimum. This allows to overcome one of the major issues with gas-sensitive mini-copters. On the other hand, remote gas sensors, most prominently Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensors have been too bulky given the payload and energy restrictions of mini-copters. Here, we present the Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS), which combines a novel lightweight TDLAS sensor with a 3-axis aerial stabilization gimbal for aiming on a versatile hexacopter. 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). It enables tomographic reconstruction of gas plumes and a localization of gas sources. We also present first results showing its performance under realistic conditions.
Pollution through emission of toxic gases is an increasing problem for the environment. It affects similarly agricultural, industrial and urban areas. In future, environmental emissions in ambient air must be monitored at even lower concentrations as nowadays. One environmental relevant compound is ammonia and its conversion product ammonium that have strong negative impact on human health and ecosystems. Most ammonia measurements in ambient air are performed in the range below 1000 nmol·mol 1 and thus there is a need for reliable traceable ammonia gas standards and in addition in situ analytical procedures for monitoring (in ambient air to avoid that thresholds are exceeded). Therefore, the use of reference materials is necessary for development accompanying test or for calibration, e. g. of structure-integrated sensors and mobile multi-gas sensors.
The developed gas standard generator produces gas mixtures that comply with the metrological traceability for ammonia gas standards in the desired environmentally relevant measurement range. The method is based on the permeation of ammonia through a membrane at constant temperature and pressure. The resulting ammonia penetrant gas flow is then mixed with a carrier gas flow to generate a gas standard flow of known concentration. The dynamic rage is enlarged by using a two dilution steps. Depending on the permeation rate, generable molar fractions are possible in the range nmol·mol-1 to a few µmol·mol-1. We present the design of an ammonia gas standard generator and first results of the characterisation of its individual components supporting the uncertainty assessment according to GUM for stable gas concentrations in this range. The relative uncertainty of the generated ammonia gas standard is smaller than 4 % (k = 2).
Im Projekt KonSens werden für die Anwendungsbei-
spiele bauteilintegrierte Sensorik für Betonkomponen-
ten und mobile Multigassensorik Sensorsysteme in
Form von Funktionsmustern entwickelt, validiert und
angewendet. Schwerpunkte liegen einerseits in der
Detektion und Bewertung von Korrosionsprozessen in
Beton und andererseits in der Detektion und Quantifi-
zierung sehr geringer Konzentrationen toxischer Gase
in der Luft. Dabei ist die Adaption der sensorischen
Methoden aus dem Labor in reale Messumgebungen
inklusive geeigneter Kommunikationstechnik ein
wichtiger Aspekt.
Innovation is the catalyst for the technology of the future. It is important to develop new and better technologies that can continuously monitor the environmental impact, e.g., for air Quality control or emission detection. In the recently at BAM developed Universal Pump Sensor Control (UPSC3) module, different components and sensors are fused. The combination of the individual components makes the UPSC3 module an excellent monitoring and reference system for the development and characterization of gas specific sensors. Measurements over long periods are possible, for mixed gas loads or for certain gas measurements. The System is part of a mobile sensor network of several sensor units, which can also be used as standalone systems.
In this paper, we introduce a nano aerial robot swarm for Indoor Air Quality (IAQ) monitoring applications such as occupational health and safety of (industrial) workplaces. The robotic swarm is composed of nano Unmanned Aerial Vehicles (UAVs), based on the Crazyflie 2.0 quadrocopter, and small lightweight Metal Oxide (MOX) gas sensors for measuring the Total Volatile Organic Compound (TVOC), which is a measure for IAQ. An indoor localization and positioning system is used to estimate the absolute 3D position of the swarm similar to GPS. A test scenario was built up to validate and optimize the swarm for the intended applications. Besides calibration of the IAQ sensors, we performed experiments to investigate the influence of the rotor downwash on the gas measurements at different altitudes and compared them with stationary measurements. Moreover, we did a first evaluation of the gas distribution mapping performance. Based on this novel IAQ monitoring concept, new algorithms in the field of Mobile Robot Olfaction (MRO) are planned to be developed exploiting the abilities of an aerial robotic swarm.