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 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 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-544005 UR - https://csac2021.sciforum.net/ 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 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 U6 - 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 -