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An Electronic Equipment with Face Recognition Capacity Oriented to Measuring the Alcoholic Level in People

  • Universidad Peruana de Ciencias Aplicadas

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

Abstract

This work proposes an equipment oriented to measuring the alcoholic level and simultaneously applying face recognition for people who enter risk places where their physical integrity can be affected due to their drunkenness state. In the state of the art, it is verified that several methods of measuring breathalyzer do not integrate the simultaneous facial recognition for the purposes of proper personnel access control and registration. It is also verified that subjective methods are applied such as the emitted smell perception, gait, the way of speaking or behavioral aspects. The proposed equipment consists of electronic devices that allow the detection of air flow and the measurement of the alcoholic level through a reduced board computer. Biometric face recognition is carried out through image processing algorithms, convolutional neural networks and support vector machines SVM, which run on a computer which is synchronized with the measurement equipment. The computer registers the recognized person in a database with the associated detected alcoholic level. For the validation of the proposed equipment, several samples of alcoholic level, delay times in the acquisition of images and the face recognition rate were evaluated. Alcohol level measurements were compared with those obtained through a certified digital breathalyzer. In this validation, Pearson's correlation coefficient was used, obtaining a value of 0.937. The maximum time delay in capturing the image during the emission of the airflow by the person was 0.067 s, while the percentage of true face recognition was higher than 95%.

Original languageEnglish
Title of host publicationApplied Technologies - Second International Conference, ICAT 2020, Proceedings
EditorsMiguel Botto-Tobar, Sergio Montes León, Oscar Camacho, Danilo Chávez, Pablo Torres-Carrión, Marcelo Zambrano Vizuete
PublisherSpringer Science and Business Media Deutschland GmbH
Pages181-194
Number of pages14
ISBN (Print)9783030715021
DOIs
StatePublished - 2021
Event2nd International Conference on Applied Technologies, ICAT 2020 - Virtual, Online
Duration: 2 Dec 20204 Dec 2020

Publication series

NameCommunications in Computer and Information Science
Volume1388 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference2nd International Conference on Applied Technologies, ICAT 2020
CityVirtual, Online
Period2/12/204/12/20

Keywords

  • Air flow
  • Alcohol level
  • Automatic detection
  • Face recognition
  • Pearson's correlation coefficient
  • Timing

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