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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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