Providing Accident Detection in Vehicular Networks through OBD-II Devices and Android-based Smart Phones

International Journal of Science and Research (IJSR), India Online ISSN: 2319-7064
Volume 2 Issue 9, September 2013
www.ijsr.net
Providing Accident Detection in Vehicular
Networks through OBD-II Devices and
Android-based Smart Phones
Narsing Rao, M1
; Suresh Kumar, V2
1
ME Student, ECE, M.V.S.R. Engineering College, Nadergul, Andhra Pradeh, India
2
Department of ECE, M.V.S.R. Engineering College, Nadergul, Andhra Pradeh, India
Abstract: Traffic accidents are one of the leading causes of fatalities in the world. An important indicator of survival rates after an
accident is the time between the accident and when emergency medical personnel are dispatched to the scene. Eliminating the time
between when an accident occurs and when first responders are dispatched to the scene decreases mortality rates by 6%.. By combining
smart phones with existing vehicles through an appropriate interface we are able to move closer to the smart vehicle paradigm, offering
the user new functionalities and services when driving. In this application we propose an Android based application that monitors the
vehicle through an On Board Diagnostics (OBD-II) interface, being able to detect accidents. The application reacts to positive detection
by sending details about the accident through SMS to pre-defined destinations, immediately followed by an automatic phone call to the
emergency services.
Keywords: OBD-II; Android smart phone; Bluetooth SPP; GPS information.
1. Introduction
In India, an increasing number of vehicles on the roads, in
recent past, have led to an increase in the number of road
accidents. There have been alarming statistics regarding the
number of accidents per day in India. At least 1,42,000
people died due to road accidents in India in the year
2011.Bad driving, lax traffic control, and poor road
conditions are the main reason for this. The ability to detect
traffic accidents using smart phones has only recently
become possible because of the advances in the processing
power and sensors deployed on smart phones. For example,
the iPhone 4 includes a GPS system for determining the
geographic position of the phone, an accelerometer for
measuring the forces applied to the phone, two separate
microphones, and a 3-axis gyroscope for detecting phone
orientation.
In this paper we propose combining existing vehicles with
smart phones to achieve a solution able to improve security
on the road. In our solution, smart phones are used as an
alternative On-Board-Unit (OBU) within the vehicle,
accessing the information in the vehicle’s internal bus
wirelessly. The only requirement to achieve this goal is that
the vehicle supports the OBD-II standard. Since this standard
is mandatory since 2001, the solution is applicable to all
vehicles aged 10 years or less (as of 2011). In this work, a
specialized smart phone application was developed to
provide support for emergency services based on the
information available in the communications bus of the
vehicle. In particular, the proposed application monitors the
vehicle’s speed and airbag triggers to detect when an
accident has occurred. Positive accident detection is followed
by any sequence of actions defined by the user, such as
sending accident details via SMS making an automated
phone call to the emergency services.
2. Literature Review
In the literature we can find some works that adopt Android
based smart phones to support all sorts of in-vehicle services.
By combining this data with measurements from the mobile
device’s sensors, a high detection rate of serious accidents
could be reached. In [1], the authors describe a system that
gathers vehicle data and sends it to a centralized database in
case of an accident. In [3], the authors present an automatic
emergency alert system for two-wheeled vehicles that
includes an accident detector inclination sensor and decision
unit and a system to inform third parties about historic data
of speed, acceleration and braking. Hernandez et al. [4]
developed a prototype of an on-board unit that allows the
driver to communicate with his vehicle, as well as with other
available devices (PDAs, cellular, sensor networks, and so
on and with the road infrastructure) in order to consume
intelligent transport services.
The work done by Hampton C. Gabler [5] reports on a
research effort which seeks to dramatically reduce
Emergency Medical Services response time by developing
and testing an Automated Crash Notification System which
automatically transmits the location and severity of a crash to
EMS personnel. Chen et al. proposed a vehicular
Android/OSGi platform that allows diagnosing or managing
the system status of a vehicular platform remotely and also to
use visual intelligence to continually update their application
services based on context awareness without user
intervention.
3. Project Overview
It consists of two main sections in the system. The first
section android smart phone which consists of Bluetooth SPP
application and ARM7 controller based On Board Diagnostic
device, where the communication between them is done
based on the Bluetooth device. The Block diagrammatic
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representation of the circuit is shown in the Fig.1.In this
work we develop an application that communicates with the
vehicle’s internal bus using the OBD-II interface and
Bluetooth communication to determine whether accidents
have occurred, and to estimate the severity of such accidents.
The information retrieved is then submitted to emergency
services, and an emergency phone call is automatically
established by the android smart phone which is shown in the
Fig.2.
Figure 1: Block diagram in Vehicular Unit.
In this work, a specialized smart phone application was
developed to provide support for emergency services based
on the information available in the communications bus of
the vehicle. In particular, the proposed application monitors
the vehicle’s speed and airbag triggers to detect when an
accident has occurred. Positive accident detection is followed
by any sequence of actions defined by the user, such as
sending accident details via SMS making an automated
phone call to the emergency services.
Figure 2: Mobile Unit.
Initially the smart phone connects to an OBD-II device via
Bluetooth to retrieve data from the vehicle’s bus. The
information gained, together with data from other sources
(e.g. GPS system) is packed and sent to an emergency
services database or to other third parties defined by the user
if an accident is detected. This procedure is followed by an
automatic call to an operator, which will send an ambulance
or other rescue services to the accident location. This is
illustrated in the following Fig 3.
Figure 3: Different interacting elements in application.
The application also offers general purpose information to
the driver, including gas levels, detection of failures in
mechanical elements, extensive engine feedback data, etc. To
understand why the proposed solution is feasible, it is worth
noticing that, despite initial OBD-II connectors relied on RS-
232 (serial port) or USB connections, now a days we can
already find in the market OBD-II connectors that provide an
application called Bluetooth SPP enabling seamless
connectivity with smart phones and all sorts of mobile
devices. Thus, it is an effective approach for reducing traffic
fatalities, therefore, is to reduce the time between when an
accident occurs and when first responders, such as medical
personnel, are dispatched to the scene of the accident.
Automatic collision notification systems use sensors
embedded in a car to determine when an accident has
occurred. These systems immediately dispatch emergency
medical personnel to serious accidents. Eliminating the time
between accident occurrence and first responder dispatch
reduces fatalities.
3.1 The OBD-II Standard
Several operating modes are defined by the OBD-II standard
to allow for an easier interaction with the system, and
defining the desired functionality. Most automobile
manufacturers have introduced additional operation modes
that are specific to their vehicles, thus offering a full control
of the available functionality. The European version of the
OBD-II standard, known as EOBD, is mandatory for all
gasoline and diesel vehicles since 2001 and 2003,
respectively. Despite it introduces small improvements
EOBD strongly resembles OBD-II, sharing the same
connectors and interfaces. Since today’s smart phones and
tablet PCs are equipped with a range of modern and highly
accurate sensors, they can also be used for analyzing driving
related scenarios. Mednis et al. developed a system that
allows the detection of potholes using a mobile device’s
built-in accelerometer (Mednis et al. 2011).
The OBD-II standard specifies the type of diagnostic
connector and its pin out, the electrical signaling protocols
available, and the messaging format. It also provides a
candidate list of vehicle parameters to monitor along with
how to encode the data for each. There is a pin in the
connector that provides power for the scan tool from the
vehicle battery, which eliminates the need to connect a scan
tool to a power source separately. However, some
technicians might still connect the scan tool to an auxiliary
power source to protect data in the unusual event that a
vehicle experiences a loss of electrical power due to a
malfunction.
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The application also offers general purpose information to
the driver, including gas levels, detection of failures in
mechanical elements, extensive engine feedback data, etc. To
understand why the proposed solution is feasible, it is worth
noticing that, despite initial OBD-II connectors relied on RS-
232 (serial port) or USB connections, now a days we can
already find in the market OBD-II connectors that provide an
application called Bluetooth SPP enabling seamless
connectivity with smart phones and all sorts of mobile
devices.
4. Implementation Details
Our application was developed for the Android platform,
now a day’s available in most smart phones in whole world.
Android-based smart phones typically include different
wireless interfaces, such as Bluetooth, WiFi, GPS and 3G,
making them ideal for our purposes. In particular, our
solution will rely on the Bluetooth technology to establish a
data between the smart phone and a Bluetooth-enabled OBD-
II interface. This application basically combines two
elements-vehicle and smart phone via Bluetooth technology.
We have to store the phone number of the first responder in
our design and a SIM should insert in the GSM module.
After storing the phone number we can get the all the sensors
information like fuel, temperature, accelerometer values
along with GPS information in the form of longitude and
latitude will be displayed on LCD and phone which is shown
In the Fig 4.
Figure 4: Displaying sensor values on phone.
The accelerometer value i.e. g value depends on the
orientation of the vehicle along three axes. If the g value less
than 1, the vehicle is moving in safe zone. If g value is
greater than 1, this indicates that vehicle met with an
accident. Then suddenly the SMS will be sent by GSM to the
first responder as shown in Fig 5. The responder notifies the
GPS information in the form of longitude and latitude values
then immediately he will inform the emergency services.
This way we can reduce the interval between when an
accident occurs and when emergency services such as 108,
medical ambulances will be reach to that particular location.
Figure 5: Message to first responder phone.
After getting an accident details in the form of longitude and
latitude along with g value, the automatic call from the
accident location will go as shown in the Fig 6.
Figure 6: An automatic call to the predefined destination.
Our proposed application contains the applications in our
daily life, like Cost efficient technique since data can be
analyzed in the mobile itself, Accident prevention and
Improving the driving efficiency and comfort.
5. System Design and Scope
As road traffic is increasing day by day, monitoring it in an
effective way has been challenge to researchers. Since smart
phones are penetrating into common people’s lives very fast,
utilizing the sensors available in them for traffic monitoring
is good idea. The data processed by the mobile can be sent to
a central server, which can use the information received to
annotate maps accessed by the users through this application.
This annotation can contain lot of information like the
intensity of traffic at a junction, the bumpy nature of the road
etc. All this can be done in an energy efficient manner by
using low energy consuming components of the mobile like
accelerometer and occasionally using GPS for localization
and finding the bearing of the road. Also, applying machine
learning techniques in classifying data can help the system to
adapt to changing factors like nature of the road and vehicle
type the users use.
The experimental setup for this project is shown in the Fig 7.
It contains an Android based application called Bluetooth
SPP that monitors the vehicle through an OBD interface
being able to detect accidents. If a vehicle met with an
accident, immediately the first responder will get the
accident details and location through SMS, followed by an
automatic call by using GSM,GPS technologies in order to
respond quickly it help at saving lives.
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The application reacts to positive detection by sending
details about the accident through SMS to pre-defined
destinations, immediately followed by an automatic phone
call to the emergency services. Experimental results using a
real vehicle show that the application is able to react to
accident events in less than 3 seconds, a very low time,
validating the feasibility of smart phone based solutions for
improving safety on the road. Since android is an open
source operating system it is easy to develop applications
using java and as well as the native language and then
converting it into the Android Classes. The idea what is been
proposed is to have a basic 1 GHz computer system running
in the car with Android operating system being the sole
controller. The system is interfaced with the vehicle ECU
and the sensors and it helps the user to have a better control
over the vehicle.
Figure 7: Hardware setup for the project.
The important hardware parts used in the above figure are,
1. ARM7 TDMI-S Processor (LPC 2148 micro controller)
2. Fuel level Sensor
3. Temperature Sensor
4. Accelerometer Sensor
5. GPS Module
6. GSM Module
7. Bluetooth
5.1 LPC 2148 Micro Controller
The LPC2141/42/44/46/48 microcontrollers are based on a
16-bit/32-bit ARM7TDMI-S CPU with real-time emulation
and embedded trace support, that combine the
microcontroller with embedded high-speed flash memory
ranging from 32 kB to 512 kB. A 128-bit wide memory
interface and unique accelerator architecture enable 32-bit
code execution at the maximum clock rate. For critical code
size applications, the alternative 16-bit Thumb mode reduces
code by more than 30 % with minimal performance penalty.
The main features are
a. 16-bit/32-bit ARM7TDMI-S microcontroller in a tiny
LQFP64 package.
b.8 kB to 40 kB of on-chip static RAM and 32 kB to 512 kB
of on-chip flash memory.
c. 128-bit wide interface/accelerator enables high-speed 60
MHz operation.
d.In-System Programming/In-Application Programming
(ISP/IAP) via on-chip boot loader software.
e. Single flash sector or full chip erase in 400 ms and
programming of 256 B in 1ms.
5.2 LM35 Temperature Sensor
LM35 converts temperature value into electrical signals.
LM35 series sensors are precision integrated-circuit
temperature sensors whose output voltage is linearly
proportional to the Celsius temperature. The LM35 requires
no external calibration since it is internally calibrated. . The
LM35 does not require any external calibration or trimming
to provide typical accuracies of ±1⁄4°C at room temperature
and ±3⁄4°C over a full −55 to +150°C temperature range.
5.3 Accelerometer Sensor
The MMA7660FC is a ±1.5 g 3-Axis Accelerometer with
Digital Output (I2C). It is a very low power, low profile
capacitive MEMS sensor featuring a low pass filter,
compensation for 0g offset and gain errors, and conversion to
6-bit digital values at user configurable samples per second.
Fuel level sensor is used to measure the level or quantity of
fuel in the fuel tank. This sensor works on the principle of
electrical capacitance, which states that, when air surrounded
electrode is immersed in the liquid it changes its capacitance.
5.4 GSM and GPS Technologies
Bluetooth wireless technology enables communication
between Bluetooth-compatible devices. It is used for short-
range connections between desktop and laptop computer. we
have used HC-04/06 Bluetooth module in order to establish
the connection between the vehicle and smart phone. A GPS
receiver (GPS634R) acquires these signals and provides the
user with information. Using GPS technology, one can
determine location in the form of latitude and longitude
which are used in this project, velocity and time, 24 hours a
day, in any weather conditions anywhere in the world for
free. Our project contains GSM module of type SIM 300
supports power supply of 3.3v-4.5v. GSM (Global System
for Mobile communications) is an open, digital cellular
technology used for transmitting mobile voice and data
services. GSM (Global System for Mobile communication)
is a digital mobile telephone system that is widely used in
Europe and other parts of the world.
Latitude is defined as a measurement of distance in degrees
north and south of the equator. There are 90 degrees of
latitude from the equator to each of the poles, north and
south. Latitude lines are parallel, that is they are the same
distance apart. The equator is the longest of all lines of
latitude. Longitude is defined as measurement of distance in
degrees east or west of the prime meridian. Longitude lines
to the left of the prime meridian give locations west, in the
western hemisphere. Longitude lines to the right of the
primer meridian give locations east, in the eastern
hemisphere.
6. Conclusion
The above idea proposed is an economic alternative to the
high budgeted cars in today's market. If given a proper
backbone to this project it would create a revolution
equivalent to the buzz what Android has created in the
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mobile phone sector. This idea is cost efficient and is more
controlled by the user than the manufacturer which would be
the one of the main reason this system would sell. To further
increase the usage of automatic accident detection and
notification systems, smart phones can be used to indirectly
detection accidents through their onboard sensors, such as
accelerometers. Many challenges must be overcome
however, particularly the potential for false positives from
accidentally dropped phones. Due to the large volume of
“phantom” (accidental) calls to emergency services, reducing
the false positive rate of smart phone accident detection is
important. Using a combination of context data, such as
determining when a user is inside a vehicle, sensor data, such
as accelerometer and acoustic information, and intelligent
sensor data filtering, accident detection systems can be
created that are resistant to false positives.
7. Future Scope
Our future work is aimed towards using advanced machine
learning techniques to find out patterns from the collected
data and classify them accordingly. This can be done on a
server where data can be uploaded at the end of the journey.
We also want to enable crowd-sourcing, to collect mass data
and analyze other subtle reasons behind rash driving, e.g.,
under what conditions - traffic, rush hours etc. a person
drives rashly. Along with this idea proposed by us we are
trying to implement this model on a small term basis and try
to experiment with other hybrids in the world of Android
development. We would come out with the implementation
of the above idea proposed if essentials pertained. Also,
applying machine learning techniques in classifying data can
help the system to adapt to changing factors like nature of
the road and vehicle type the users use.
References
[1] US Patent 7133661, ―Emergency information
notifying system, and apparatus, method and moving
object utilizing the emergency information notifying
systemǁ, 2006.
[2] FP7 SCP8-GA-2009-233976, “SAFETRIP: Satellite
Applications For Emergency handling, Traffic alerts,
Road safety and Incident Prevention,”2010.
[3] E. Dávila, ―eCall: status of the initiativeǁ, 2nd PSAPs
Expert Group meeting. Brussels, April 2007.
[4] U. Hernandez, A. Perallos, N. Sainz, and I. Angulo,
―Vehicle on board platform: Communications test and
proto-typing,ǁ in Intelligent Vehicles Symposium (IV),
2010 IEEE, pp. 967 –972, 2010.
[5] Hampton C Gabler, Bergasa, J. Nuevo, M. Sotelo, R.
Barea, and M. Lopez. Real-time system for monitoring
driver vigilance. IEEE Transactions on Intelligent
Transportation Systems, 7(1):63 –77, 2006.
Author Profile
M Narsingrao received B. Tech degree in Electronics
and Communication Engineering from J.N.T.U
Hyderabad in 2010. Presently he is doing M.E from
M.V.S.R engineering college affiliated to Osmania
University in E.C.E. He has taken Embedded Systems
and VLSI Design as a specialization.
Paper ID: 11091305 257

Providing Accident Detection in Vehicular Networks through OBD-II Devices and Android-based Smart Phones

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