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%.