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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Bibliographic Details
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
Online Access:Get full text
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Description
Summary:•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.
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ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2013.10.005