ABSTRACT
As vehicle manufacturers continue to
increase their emphasis on safety with advanced driver-as assistance systems
(ADASs), we propose a device that is not only already in abundance but portable
enough as well to be one of the most effective multipurpose devices that are
able to analyze and advise on safety conditions. Mobile smart phones today are
equipped with numerous sensors that can help to aid in safety enhancements for
drivers on the road. In this paper, we use the three-axis accelerometer of an
Android-based smart phone to record and analyze various driver behaviors and
external road conditions that could potentially be hazardous to the health of
the driver, the neighboring public, and the automobile. Effective use of these
data can educate a potentially dangerous driver on how to safely and
efficiently operate a vehicle. With real-time analysis and auditory alerts of
these factors, we can increase a driver’s overall awareness to maximize safety.
ARCHITECTURE:
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.
EXISTING SYSTEM:
Analysis of
external sensors data for vehicle performance is a large area of study. Some
work has been done in the form of theoretical research and development in a
practical design. The main ideas of our work focus on mapping anomalies of a
road’s surface and classifying different driving behaviors. There has been some
work in the field of road analysis, specifically road anomaly detection.
Nericell [1] is a system researched and developed by Microsoft that detects
traffic honking, bumps, and vehicle braking using external sensors. For
detection, it uses multiple external sensors such as a microphone, GPS,
accelerometer, and Global System for Mobile communications radio for traffic
localization. Pothole Patrol [15] is another system that monitors road
conditions using GPS and an external accelerometer. The system was deployed for
testing in taxis using a convenient method to identify fatigued surfaces of a
road.
PROPOSED SYSTEM:
In this paper, we use the three-axis
accelerometer of an Android-based Smartphone to record and analyze various
driver behaviors and external road conditions that could potentially be
hazardous to the health of the driver, the neighboring public, and the
automobile. Effective use of these data can educate a potentially dangerous
driver on how to safely and efficiently operate a vehicle. With real-time analysis
and auditory alerts of these factors, we can increase a driver’s overall
awareness to maximize safety.
MODULES:
ü Device
Background module
ü Phone
Orientation and Location module
ü Road Anomaly
Detection module
ü Sending data Alert SMS module
MODULES DESCRIPTION:
Device Background
Our work
reveals to identify not only potholes but also bumps and rough, uneven, and
smooth roads using multiple axes of the accelerometer. We also utilized a
single measuring device rather than expensive external sensors placed in
numerous places around the vehicle, which ultimately increases infrastructure
costs. Our device, which is a mobile Smartphone, contains GPS, microphones, and
an accelerometer offering flexibility in methodology and user implementation.
Encouraging results in identifying numerous road anomalies and sudden driving
maneuvers allow for our system to evaluate an entire road’s condition and help
advice drivers on unsafe characteristics, respectively, both of which are
distinguishable factors that can determine safety on the road.
ü Accelerometer sensor is going to sense
x, y & z direction value.
ü If the vehicle is moving in normal
position, then it will show x & y direction values.
ü If vehicle is out of control, then it
will follow x, y & z direction.
Phone Orientation and Location
The orientation of the phone is a
variable that may be constantly changing with the movement of the vehicle, and
so might be arbitrarily placed inside the vehicle when the driver enters. The
phone’s orientation for each experiment remained the same, with the y-axis
pointing toward the front of the vehicle and the screen (z-axis) facing
the roof. A holster that was provided with the phone was used along with Velcro
to secure the phone to the vehicle’s surface. To obtain appropriate data, the
phone was tested in multiple locations for each experiment before a final
decision was declared.
Road Anomaly Detection
Poor road conditions can lead to
replacement methods that can cause an increase in both traffic congestion and
travel time. A distressed road can also increase the chance of an accident. By
expanding on work presented in [1] and [15], we extended road anomaly detection
using a mobile phone’s accelerometer. The embedded accelerometer is capable of
detecting subtle or extreme vibrations experienced inside the vehicle. For
example, vibrations experienced as jerks can be caused by potholes or a
rugged/damaged road from a rough road. Speed bumps and potholes are two
nuisances that plague drivers on the road every day. Using a Smartphone, we
look for these road characteristics using a combination of the x-axis
and z-axis of the accelerometer. When a vehicle experiences a bump, it
ascends onto the bump, resulting in a quick rise or spike in the value of the z-axis.
This also results in a subsequent increase in the x-axis, depending on
the bump formation. At high speeds, the spike in the value of the z-axis
is very prominent. However, for low speeds, this rise is not as obvious but
still leaves an apparent impact. To detect bumps at low speeds, we compensate
with the x-axis and a dynamic threshold based on speed. If the
difference between two consecutive acceleration values of the z-axis
exceeds the threshold, as well as an x-axis threshold, a bump can be
assumed [15]. Differentiating a pothole from a bump can be a difficult task
using only a z-axis threshold, as seen in [15], but both are
distinguishable using this method. We visually illustrate this method with a
bump formation in the z-axis with gravity, whereas we also show the secondary
technique without gravity using the x-axis to help differentiate a bump
from a pothole.
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:
Ø
System : Pentium
IV 2.4 GHz.
Ø
Hard
Disk : 40 GB.
Ø
Floppy
Drive : 1.44 Mb.
Ø
Monitor : 15 VGA Colour.
Ø
Mouse : Logitech.
Ø
Ram : 512 Mb.
SOFTWARE
REQUIREMENTS:
Ø Operating
system : Windows XP.
Ø
Coding Language :
Java 1.6
Ø
Tool Kit : Android 2.2
Ø
IDE : Eclipse
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