Alcohol consumption detection through behavioural analysis using intelligent systems

•We instrumented a realistic driving simulator and monitored users behaviour.•We generated features and associated those to various BAC values.•We were able to classify drunk and sober example from 1 subject.•With multiple subjects we could estimate the BAC.•The system is generic and should adapt we...

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Published in:	Expert systems with applications Vol. 41; no. 5; pp. 2574 - 2581
Main Authors:	Robinel, Audrey, Puzenat, Didier
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier Ltd 01.04.2014 Elsevier
Subjects:	Alcohols Applied sciences Artificial intelligence Artificial neural networks Automated behavioural analysis Behavioural Blood Blood alcohol content Computer science; control theory; systems Computer systems and distributed systems. User interface Connectionism. Neural networks Data processing. List processing. Character string processing Exact sciences and technology Expert systems Human computer interface Instrumentation Intelligent systems Memory organisation. Data processing Monitors Regression Software Tasks Trains Blood alcohol content Instrumentation Automated behavioural analysis Intelligent systems Human computer interface Artificial neural networks Consumption Alcohol Regression analysis Neural network Multiple regression Aggregate model Learning systems Behavioral analysis User interface Alcoholemia Automatic analysis System analysis Artificial intelligence Intelligent system Multiple classification
ISSN:	0957-4174, 1873-6793
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Abstract	•We instrumented a realistic driving simulator and monitored users behaviour.•We generated features and associated those to various BAC values.•We were able to classify drunk and sober example from 1 subject.•With multiple subjects we could estimate the BAC.•The system is generic and should adapt well to other problems. We describe in this paper a new methodology for blood alcohol content (BAC) estimation of a subject. Rather than using external devices to determine the BAC value of a subject, we perform a behaviour analysis of this subject using intelligent systems. We monitor the user’s actions in an ordinary task and label those data to various measured BAC values. The obtained data-set is then used to train learning systems to detect alcoholic consumption and perform BAC estimation. We obtain good results on a mono-user base, and lower results with multiple users. We improve the results by combining multiple classifiers and regression algorithms.
AbstractList	We describe in this paper a new methodology for blood alcohol content (BAC) estimation of a subject. Rather than using external devices to determine the BAC value of a subject, we perform a behaviour analysis of this subject using intelligent systems. We monitor the user's actions in an ordinary task and label those data to various measured BAC values. The obtained data-set is then used to train learning systems to detect alcoholic consumption and perform BAC estimation. We obtain good results on a mono-user base, and lower results with multiple users. We improve the results by combining multiple classifiers and regression algorithms. •We instrumented a realistic driving simulator and monitored users behaviour.•We generated features and associated those to various BAC values.•We were able to classify drunk and sober example from 1 subject.•With multiple subjects we could estimate the BAC.•The system is generic and should adapt well to other problems. We describe in this paper a new methodology for blood alcohol content (BAC) estimation of a subject. Rather than using external devices to determine the BAC value of a subject, we perform a behaviour analysis of this subject using intelligent systems. We monitor the user’s actions in an ordinary task and label those data to various measured BAC values. The obtained data-set is then used to train learning systems to detect alcoholic consumption and perform BAC estimation. We obtain good results on a mono-user base, and lower results with multiple users. We improve the results by combining multiple classifiers and regression algorithms.
Author	Robinel, Audrey Puzenat, Didier
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Keywords	Blood alcohol content Instrumentation Automated behavioural analysis Intelligent systems Human computer interface Artificial neural networks Consumption Alcohol Regression analysis Neural network Multiple regression Aggregate model Learning systems Behavioral analysis User interface Alcoholemia Automatic analysis System analysis Artificial intelligence Intelligent system Multiple classification
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References_xml	– reference: Robinel, A., & Puzenat, D. (2012). Real time drunkenness analysis in a realistic car simulation. In – reference: Renault. “R-link” tactile car computer. – reference: (pp. 431–436). I6doc.com publ., April. available from – volume: 8 start-page: 357 year: 2002 end-page: 377 ident: b0050 article-title: real-time eye gaze and face pose tracking for monitoring driver vigilance publication-title: Real-Time Imaging – reference: Shimizu, S., Hiroaki, I., Hiroyuki, N., Noboru, T., Fumikazu, M., Nobuhide, H., et al. (2013). Basic study for new assistive system based on brain activity during car driving. In – volume: XXVI start-page: 778 year: 1927 end-page: 783 ident: b0010 article-title: Drunkenness, a quantitative study of acute alcoholic intoxication publication-title: California and Western Medicine – reference: (pp. 326–331) (October). – reference: (pp. 85–90). 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Snippet	•We instrumented a realistic driving simulator and monitored users behaviour.•We generated features and associated those to various BAC values.•We were able to... We describe in this paper a new methodology for blood alcohol content (BAC) estimation of a subject. Rather than using external devices to determine the BAC...
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SubjectTerms	Alcohols Applied sciences Artificial intelligence Artificial neural networks Automated behavioural analysis Behavioural Blood Blood alcohol content Computer science; control theory; systems Computer systems and distributed systems. User interface Connectionism. Neural networks Data processing. List processing. Character string processing Exact sciences and technology Expert systems Human computer interface Instrumentation Intelligent systems Memory organisation. Data processing Monitors Regression Software Tasks Trains
Title	Alcohol consumption detection through behavioural analysis using intelligent systems
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