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Mobile Phone Based Drunk Driving Detection


Published on Sep 16, 2019

Abstract

Drunk driving, or officially driving under the Influence (DUI) of alcohol, is a major cause of traffic accidents throughout the world. In this, 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 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 sends a message to predefined number in application for help well before accident actually happens

FEATURES:

· Uses the accelerometer sensors from Android mobile to match the Drunk and drive pattern.

· Automatically sends a message for Help.

· Displays on the Screen a message.

ANDROID:

Android is a software stack for mobile devices that includes an operating system, middleware and key applications. The Android SDK provides the tools and APIs necessary to begin developing applications on the Android platform using the Java programming language.

ARCHITECTURE:

Drunk Driving Detection

Drunk Driving Detection

WORKING PROCEDURE:

Drunk Driving Detection

MODULES

1) Lateral Acceleration Pattern Matching

2) Longitudinal Acceleration Pattern Matching

3) Multiple Round Pattern Matching

4) Detection Performance

5) Sending data Alert SMS

MODULES DESCRIPTION:

1) Lateral Acceleration Pattern Matching

The lateral acceleration pattern matching is based on the value of Alat. The pattern which shows remarkable changes of acceleration values reveals the abnormal curvilinear movements of the vehicle. That is when the vehicle is making the curvilinear movement, it has a sudden lateral acceleration toward one side, and then a lateral acceleration toward the other side.

2) Longitudinal Acceleration Pattern Matching

Similarly, the longitudinal acceleration pattern matching is based on the value of Alon. The problems in speed control, i.e. the vehicle acts abnormally in either accelerating or decelerating direction, result in a large absolute value of Alon, making a salient convex or concave shape in its graph of curves.

3) Multiple Round Pattern Matching

Multiple round pattern matching will increase the accuracy of drunk driving detection. The cues related to problems of lane position maintenance or problems of speed control provide evidences of drunk driving. The single lateral acceleration pattern matching or longitudinal acceleration pattern matching can indicate these two kinds of problems respectively. Each of the two detection algorithms based on the above two acceleration patterns may achieve a fairly high detection accuracy, above 50% in most cases, and around 45% in some cases. Nevertheless, the combination of observed cues from lane position maintenance and speed control problems can provide much stronger evidence for drunk driving. So we use multiple round pattern matching in the detection algorithm design.

4) Detection Performance

We study the performance of detecting drunk driving related behaviors, since drunk driving can be directly inferred by the accurate detection of these abnormal driving behaviors. We measure the detection performance in terms of false negative (FN) and false positive (FP). False negative happens when drunk driving related behaviors show up but the device misses them. False positive happens when the device reports drunk driving related behaviors but the vehicle is actually under regular driving conditions. In general, the lower the both FN and FP are, the better the performance is.

5) Sending data Alert SMS

In this module, based on the variation of directions an alert messages is sent to the Owner with a data say car number or any etc.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

 System : Pentium IV 2.4 GHz.

 Hard Disk : 40 GB.

 Monitor : 15 VGA Colour.

 Mouse : Logitech.

 Ram : 512 Mb.

 Mobile : Android Mobile

SOFTWARE REQUIREMENTS:

 Operating system : Windows XP.

 Coding Language : Java 1.6

 Tool Kit : Android 2.2

 IDE : Eclipse

CONCLUSION:

In this paper, we present a highly efficient mobile phone based drunk driving detection system. The mobile phone, which is placed in the vehicle, collects and analyzes the data from its accelerometer sensors to detect any abnormal or dangerous driving maneuvers typically related to driving under alcohol influence and sends a message for help.








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