Drunk driving, or officially Driving Under the Influence (DUI) of alcohol, is a major cause of traffic accidents throughout the world. In this paper, we propose a highly efficient system aimed at early detection and alert of dangerous vehicle maneuvers typically related to drunk driving. The entire solution requires only a mobile phone placed in vehicle and with accelerometer and orientation sensor. A program installed on the mobile phone computes accelerations based on sensor readings, and compares them with typical drunk driving patterns extracted from real driving tests. Once any evidence of drunk driving is present, the mobile phone will automatically alert the driver or call the police for help well before accident actually happens. We implement the detection system on Android G1 phone and have it tested with different kinds of driving behaviors. The results show that the system achieves high accuracy and energy efficiency.
Description
IEEE Xplore Abstract - Mobile phone based drunk driving detection
%0 Conference Paper
%1 5482295
%A Dai, Jiangpeng
%A Teng, Jin
%A Bai, Xiaole
%A Shen, Zhaohui
%A Xuan, Dong
%B Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2010 4th International Conference on-NO PERMISSIONS
%D 2010
%K activityrecognition sensors
%P 1-8
%R 10.4108/ICST.PERVASIVEHEALTH2010.8901
%T Mobile phone based drunk driving detection
%U http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5482295
%X Drunk driving, or officially Driving Under the Influence (DUI) of alcohol, is a major cause of traffic accidents throughout the world. In this paper, we propose a highly efficient system aimed at early detection and alert of dangerous vehicle maneuvers typically related to drunk driving. The entire solution requires only a mobile phone placed in vehicle and with accelerometer and orientation sensor. A program installed on the mobile phone computes accelerations based on sensor readings, and compares them with typical drunk driving patterns extracted from real driving tests. Once any evidence of drunk driving is present, the mobile phone will automatically alert the driver or call the police for help well before accident actually happens. We implement the detection system on Android G1 phone and have it tested with different kinds of driving behaviors. The results show that the system achieves high accuracy and energy efficiency.
@inproceedings{5482295,
abstract = {Drunk driving, or officially Driving Under the Influence (DUI) of alcohol, is a major cause of traffic accidents throughout the world. In this paper, we propose a highly efficient system aimed at early detection and alert of dangerous vehicle maneuvers typically related to drunk driving. The entire solution requires only a mobile phone placed in vehicle and with accelerometer and orientation sensor. A program installed on the mobile phone computes accelerations based on sensor readings, and compares them with typical drunk driving patterns extracted from real driving tests. Once any evidence of drunk driving is present, the mobile phone will automatically alert the driver or call the police for help well before accident actually happens. We implement the detection system on Android G1 phone and have it tested with different kinds of driving behaviors. The results show that the system achieves high accuracy and energy efficiency.},
added-at = {2015-02-03T17:53:17.000+0100},
author = {Dai, Jiangpeng and Teng, Jin and Bai, Xiaole and Shen, Zhaohui and Xuan, Dong},
biburl = {https://www.bibsonomy.org/bibtex/2ce27e826b918f5356df90c806fd12c1a/lutful_kabir},
booktitle = {Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2010 4th International Conference on-NO PERMISSIONS},
description = {IEEE Xplore Abstract - Mobile phone based drunk driving detection},
doi = {10.4108/ICST.PERVASIVEHEALTH2010.8901},
interhash = {68d9d424f52fb358237d4f14b4513c63},
intrahash = {ce27e826b918f5356df90c806fd12c1a},
keywords = {activityrecognition sensors},
month = {March},
pages = {1-8},
timestamp = {2015-02-03T17:53:17.000+0100},
title = {Mobile phone based drunk driving detection},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5482295},
year = 2010
}