An ANN-BP based Multi-Alcohol Classification Model Through Different QCM Gas Sensors

Aiman Sultan, Asif Masood, Shahzaib Tahir, Fawad Khan, Ahmed Raheeq Sultan

Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review


Alcohol content detection provides several advantages and is crucial in research encompassing product and business development. The findings of a sensor's precise detection cannot be immediately classified; instead, they need to be processed further to identify the proper type of alcohol. A quartz crystal microbalance (QCM) is one among many sensors that can identify various types of alcohol. In order to identify numerous categories of alcohols, this paper presents an ANN-BP based model trained over 5 different datasets of QCM 3, QCM 6, QCM 7, QCM 10, and QCM 12. The ANN-BP model employs keras optimizer, one-hot encoding to display results and is trained via a fixed learning rate. In this article, five different forms of alcohol are used i.e., 1-octanol, 1-propanol, 2-butanol, and 1-isobutanol. The model is run through several epochs of training with a learning rate of 0.01 and the impact of loss and accuracy with respect to the number of epochs is discussed in detail. The performance analysis of the classification of the test set is carried out by plotting the confusion matrix as well as the metrics of precision, recall, accuracy, and f1 score. The model is also trained by alteration of different hyperparameters and analysis is carried out based on their results.

Original languageEnglish
Title of host publication2023 International Conference on Communication Technologies (ComTech)
Place of Publication979-8-3503-3722-8
Number of pages6
ISBN (Electronic)9798350337211
Publication statusPublished - 4 Jul 2023
Externally publishedYes
Event2023 International Conference on Communication Technologies - Military College of Signals, Rawalpindi, Pakistan
Duration: 15 Mar 202316 Mar 2023


Conference2023 International Conference on Communication Technologies
Abbreviated titleComTech

Bibliographical note

Publisher Copyright:
© 2023 IEEE.


  • Artificial Neural Network
  • Back propagation
  • QCM sensors
  • alcohol classification
  • confusion matrix
  • f1 score

ASJC Scopus subject areas

  • Information Systems and Management
  • Information Systems
  • Instrumentation
  • Health Informatics
  • Hardware and Architecture
  • Computer Networks and Communications


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