Non-Intrusive Drunk Detection Test Using Smart Phone
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 6
Abstract
In India every year there are large number of fatalities in road accidents, a vast of them are due to drunken driving. The study investigated the anomalies in the gait pattern incurred after consuming alcohol. The proposed algorithm helps to alert the driver and to report the concerned authorities so that a suitable action can be taken against the driver as soon as anomalies are found. The study was conducted on 12 subjects including 7 bus drivers and 5 truck drivers who drive the vehicle on an average of 10 hours and 16 hours per day respectively. All the drivers were from Punjab, India. The anomalies were investigated by using accelerometer sensor integrated in the smart phone. The effect of alcohol on the parameters was evaluated by comparing the variance of gait stretch and step time. The listed parameters were analysed on PC after extracting the data from smart phone via Sensor UDP android app. The consumption of alcohol resulted in increase of mean variance of step time to 28 sec and 30 sec from 7 sec and 8 sec and of gait stretch to 2.25m/s2 and 6 m/s2 from 1.75 m/s2 and 4 m/s2 in case of Bus drivers and truck drivers respectively. This study highlights an efficient and nonintrusive method to detect the drivers under the influence of alcohol and thus would help to reduce the accidents.
Authors and Affiliations
Anubhav Goyal, Dr Suman Kant, Dr Parveen Kalra, Ishant Gupta
Keywords
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