TY - GEN
T1 - An Electronic Equipment with Face Recognition Capacity Oriented to Measuring the Alcoholic Level in People
AU - Merino, Luis
AU - Chavesta, Wilson
AU - Kemper, Guillermo
AU - Lau, Kalun
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - 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%.
AB - 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%.
KW - Air flow
KW - Alcohol level
KW - Automatic detection
KW - Face recognition
KW - Pearson's correlation coefficient
KW - Timing
UR - https://www.scopus.com/pages/publications/85107327775
U2 - 10.1007/978-3-030-71503-8_14
DO - 10.1007/978-3-030-71503-8_14
M3 - Contribución a la conferencia
AN - SCOPUS:85107327775
SN - 9783030715021
T3 - Communications in Computer and Information Science
SP - 181
EP - 194
BT - Applied Technologies - Second International Conference, ICAT 2020, Proceedings
A2 - Botto-Tobar, Miguel
A2 - Montes León, Sergio
A2 - Camacho, Oscar
A2 - Chávez, Danilo
A2 - Torres-Carrión, Pablo
A2 - Zambrano Vizuete, Marcelo
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd International Conference on Applied Technologies, ICAT 2020
Y2 - 2 December 2020 through 4 December 2020
ER -