AI-driven 5G IoT e-nose for whiskey classification

Jaume Segura-Garcia; Rafael Fayos-Jordan; Mohammad Alselek; Sergi Maicas; Miguel Arevalillo-Herraez; Enrique A. Navarro-Camba; Jose M. Alcaraz Calero

doi:10.1007/s10489-025-06425-1

AI-driven 5G IoT e-nose for whiskey classification

Jaume Segura-Garcia, Rafael Fayos-Jordan, Mohammad Alselek, Sergi Maicas, Miguel Arevalillo-Herraez, Enrique A. Navarro-Camba, Jose M. Alcaraz Calero

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Abstract

The main contribution is the design, implementation and validation of a complete AI-driven electronic nose architecture to perform the classification of whiskey and acetones. This classification is of paramount important in the distillery production line of whiskey in order to predict the quality of the final product. In this work, we investigate the application of an e-nose (based on arrays of single-walled carbon nanotubes) to the distinction of two different substances, such as whiskey and acetone (as a subproduct of the distillation process), and discrimination of three different types of the same substance, such as three types of whiskies. We investigated different strategies to classify the odor data and provided a suitable approach based on random forest with accuracy of 99% and with inference times under 1.8 seconds. In the case of clearly different substances, as subproducts of the whiskey distillation process, the procedure presented achieves a high accuracy in the classification process, with an accuracy around 96%.

Original language	English
Article number	686
Number of pages	14
Journal	Applied Intelligence
Volume	55
DOIs	https://doi.org/10.1007/s10489-025-06425-1
Publication status	Published - 24 Apr 2025

Bibliographical note

Copyright © The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/

Funding

This research was funded by UKRI EPSRC EP/Y028813/1 “National Edge AI Hub for Real Data: Edge Intelligence for Cyberdisturbances and Data Quality.” Also, thank to the Generalitat Valenciana for the grant CIBEST/2023/101 and the grant CIAEST/2022/91. It has been also partially supported by the Spanish Ministry of Science and Innovation/Spanish Research Agency (MCIN/AEI) within the project Agriculture 6.0 with reference TED2021-131040B-C33 and the project ECO4RUPA with reference PID2021-126823OB-I00, funded by MCIN/AEI/10.13039/501100011033 and by the European Union “NextGenerationEU”/PRTR.

Keywords

5G IoT
e-nose
PCA
ML
Odor discrimintation

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10.1007/s10489-025-06425-1Licence: CC BY 4.0

J Segura-Garcia et al_AI-driven 5G IoT e-nose for whiskey classification
Copyright © The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/
Final published version, 1.46 MBLicence: CC BY 4.0

Cite this

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AI-driven 5G IoT e-nose for whiskey classification

Abstract

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Keywords

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