Machine Learning-enabled Biomimetic Electronic Olfaction Using Graphene Single-channel Sensors
Huang S, Croy A, Bierling A, Panes-Ruiz LA, Ibarlucea B, Cuniberti G (2022)
Publication Type: Conference contribution
Publication year: 2022
Publisher: Institute of Electrical and Electronics Engineers Inc.
Conference Proceedings Title: International Symposium on Olfaction and Electronic Nose, ISOEN 2022 - Proceedings
Event location: Aveiro, PRT
ISBN: 9781665458603
DOI: 10.1109/ISOEN54820.2022.9789605
Abstract
Olfaction is an evolutionary old sensory system, yet it provides sophisticated access to information about our surroundings. Inspired by the biological example, electronic noses (e-noses) in combination with efficient machine learning techniques aim to achieve similar performance and thus digitize the sense of smell. Despite the significant progress of e-noses, their development remains challenging due to the complex layout design of sensor arrays with a multitude of receptor types or sensor materials, and the need for high working temperature. In the current work, we present the discriminative recognition of odors utilizing graphene single-channel nanosensor-based electronic olfaction in conjunction with machine learning techniques. Multiple transient features extracted from the sensing response profile are employed to represent each odor and used as a fingerprint of odors. The developed electronic olfaction prototype exhibits excellent odor identification performance at room temperature, maximizing the obtained results from a single nanosensor. The developed platform may facilitate miniaturization of e-nose systems, digitization of odors, and distinction of volatile organic compounds (VOCs) in various emerging applications.
Involved external institutions
Germany (DE)How to cite
APA:
Huang, S., Croy, A., Bierling, A., Panes-Ruiz, L.A., Ibarlucea, B., & Cuniberti, G. (2022). Machine Learning-enabled Biomimetic Electronic Olfaction Using Graphene Single-channel Sensors. In International Symposium on Olfaction and Electronic Nose, ISOEN 2022 - Proceedings. Aveiro, PRT: Institute of Electrical and Electronics Engineers Inc..
MLA:
Huang, Shirong, et al. "Machine Learning-enabled Biomimetic Electronic Olfaction Using Graphene Single-channel Sensors." Proceedings of the 2022 IEEE International Symposium on Olfaction and Electronic Nose, ISOEN 2022, Aveiro, PRT Institute of Electrical and Electronics Engineers Inc., 2022.
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