A drug identification system for intoxicated drivers based on a systematic review

  1. GONZÁLEZ, Alfonso 1
  2. RAMOS, Juan 1
  3. DE PAZ, Juan F. 1
  1. 1 Universidad de Salamanca
    info

    Universidad de Salamanca

    Salamanca, España

    ROR https://ror.org/02f40zc51

Revue:
ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal

ISSN: 2255-2863

Année de publication: 2015

Volumen: 4

Número: 4

Pages: 83-101

Type: Article

DOI: 10.14201/ADCAIJ20154483101 DIALNET GOOGLE SCHOLAR lock_openAccès ouvert editor

D'autres publications dans: ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal

Objectifs de Développement Durable

Résumé

Tests to detect the use of illegal substances among drivers are becoming more common. During these tests, a saliva test is performed and agents observe the driver to determine whether or not they are driving under the influence of psychoactive substances. During the joint control of alcohol and drugs, a breath test is performed followed by a saliva test. In addition, agents use a previously established observation questionnaire to evaluate external signs that the driver may present. This review aims to help expand and improve the questionnaire administered by the traffic officer to the driver, so that upon completing the questionnaire as indicated, it is possible to determine which drug corresponds to the symptoms displayed by the driver. The diagnosis will be facilitated by a software tool that employs the use of decision trees whose gain function has been modified to give different weights to signs and methods. A study was conducted on the symptoms and observable and/or easily detectable signs of drugs detected at sobriety checkpoints. This has enabled the creation of a test that determines the substance consumed by the driver. The proposal facilitates the detection of drugs with the data gathered from the test.

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