202_camera ready_RTEICT_16_prasanth (1)

IEEE International Conference On Recent Trends In Electronics Information Communication Technology, May 20-21, 2016, India
978-1-5090-0774-5/16/$31.00 © 2016 IEEE
An HUD for Connected Car for Maintenance and
Emergency Intimation
1
Prasanth R,2
Aaradhana A. Deshmukh,3
Bala Vignesh and4
Janani R
1,3
Department of Electronics and Communication Engineering,
Vel Tech Dr. RR& Dr. SR Technical University, Chennai, Tamil Nadu, India
2
Department of Computer Science Engineering,
Smt. Kashibai Navale College of Engineering, Pune, Maharastra, India
4
Department of Electronics and Instrumentation Engineering,
Valliammai Engineering College, Chennai, Tamil Nadu, India
Email: 1
ragaprasanth@gmail.com, 2
aadeshmukhskn@gmail.com, 3
balavignesh@veltechuniv.edu.in, 4
jananihema95@gmail.com
Abstract— This study deals with the development of
vision for vehicle and driver to prevent problems for both
vehicle and driver while driving. Wireless communication
in car is the booming field of Network communication. An
Head-up-Display is developed for calculating the car
strategies which help in maintenance and life time of the
car to analyze the system with the help of CAN (Controller
Area Network) used for communication inside the ECU
(Electronic Control Unit) from ELM327 Bluetooth
analyzer. And a pulse sensor is connected to the processor
to analyze and send immediate signal to the emergency
contacts in the time of abnormal conditions of the person
while driving. By using Node-Red in the communication
will lead the communication easier for the person using
and implementing the HUD will lead the maintenance of
the system good.
Keywords— OBD-II; Raspberry Pi; Pulse Sensor; ELM-327;
CAN; Node-Red.
I. INTRODUCTION
With the development of Technologies for the vehicles in
modern world. A Car has many control units by the
development of automotive electronics technology like
Electronic Control Units (ECU) and devices like Engine
Electronic Controller (EEC), Electronic Transmission
Controller (ETC) and some digital instruments to satisfy the
requirement of the system of environment protection,
decreasing fuel consumption and increasing safety and
comfort of passenger vehicle [1]. So, with the help of
ELM327 Bluetooth analyzer the Controller Area Network
(CAN) is used to control the above mentioned units
collectively. The Bluetooth analyzer will give the output of the
CAN by CANLOW and CANHIGH pin through the Bluetooth
device connected to it. By using the Bluetooth receiver
connected to Raspberry Pi we analyze the data and written an
Graphical User Interface (GUI) with help of python script
through which the CAN output is shown in the screen of the
raspberry pi which is fixed as an HUD in the car.
The IOT implementation comes in the part for the real
time monitoring of the health condition of the driver of the car
by using Node-Red in the Raspberry Pi which is a code-less
platform for developing IOT applications. In this the pulse
sensor is connected to the raspberry pi fixed in the seat belt of
the driver, which continuously monitors the pulse of the
driver. When the pulse variation is abnormal that occurs in the
condition of anxiety or real health problems which will lead to
definite accident. So, by the detection of variation in pulse an
emergency message like GPS co-ordinates or text messages
can be sent to the concerned emergency contacts for help.
A betterment idea for maintaining the vehicle and driver
health monitoring for a safety travel is introduced.
II. BACKGROUND RELATED WORK
A. Overview of ELM 327
ELM-327 is a programmed microcontroller used for On
Board Diagnostics as an interface in every modern car
available in market. No matter how you physically connect to
the ELM327, one will need a way to send and receive data.
The simplest method is to use the ‘terminal’ programs that are
available [2]. Here with the Linux terminal the port is
connected with Bluetooth communication and data are
collected in the terminal. The protocols supported by the ELM
327 are
1. SAE J1850 PWM (41.6 Kbit/s)
2. SAE J1850 VPW (10.4 Kbit/s)
3. ISO 9141-2 (5 baud init, 10.4 Kbit/s)
4. ISO 14230-4 KWP (5 baud init, 10.4 Kbit/s)
5. ISO 14230-4 KWP (fast init, 10.4 Kbit/s)
6. ISO 15765-4 CAN (11 bit ID, 500 Kbit/s)
10. SAE J1939 (250kbps)
11. SAE J1939 (500kbps)
Here we deal with the CAN protocol for collecting the data.

978-1-5090-0774-5/16/$31.00 © 2016 IEEE
B. OBD-II PID
PID is Parameter ID of the vehicle ECU (Electronic Control
Unit) which was the codes used to request the data from the
diagnostic tool. They work with hex mode of data and
support the protocol of SAE J1939. They have 10 modes of
operations i.e. (01-0A).
III. IMPLEMENTATION METHOD
A. Development of GUI
A graphical user interface is developed in the raspberry
PI by using Python scripts, because python is the fast and
reliable platform for development in pi and this GUI will
help in display of the sensor data collected from the car
through OBD-II device in this first step of getting the data is
to collect the data and display the data. The data which was
transmitted by the ELM-327 through bluetooth and the
signal from the bluetooth is collected through a bluetooth
receiver which was connected to the raspberry pi, here in
Fig. 1 where the GUI is developed according to the data
received.
Fig. 1. GUI for User Screen
B. Connection of ELM
ELM 327 works with different mode of PID’S and supports
different protocols. Here we have discussed with the SAE
J1939 protocol which is basically CAN (Controller Area
Network) which has to basic communication ports like CAN L
and CAN H, low and high pins for sharing the data collected
generally form the bus [5]. Fig. 2 shows the working of CAN
network in a bus. This device will help for collecting the data
from the car, it is just a microcontroller which was coded with
CAN protocol and connected to the CAN bus of the car so,
which will lead in the transmission of data from the car.
Fig. 2. CAN Communication
C. Implementing Node flow:
The node flow was done as the second part for safety
measures in which the heart rate of the person is measured and
a loop is developed in the java script with the help of NODE-
RED and the variation in the pulse will be intimated to the
emergency contacts with help of mobile app contributed nodes.
Fig. 3 is a basic node flow which shows the transmission of
data.
Fig. 3. Basic Node Flow in NODE-RED
IV. WORKING METHOD OF PRODUCT
A. Execution of OBD Script in PI
After connecting the OBD-II device that is ELM327 in the
16 pin port present in the modern cars, raspberry pi is
connected to the Bluetooth device to communicate with the
diagnosing device.
a) Implementing the python and bluetooth
Raspberry pi is the smart and small computer used for
embedded applications. In which nowadays it comes with pre-
installed python scripting because they were used for less
memory usage and fast execution time. Bluetooth drivers if it is
not it can be done in the following steps.
# apt-get install Bluetooth bluez blueman
# apt-get install python
# apt-get install python tools
b) Code for Graphical User Interface
The code was written in the python script for less
memory usage and easy scripting with the help of libraries
written by the free obd master. Through which they used to
develop the software for the windows or Linux systems which
were used in the service centers and the tools they connect to
the diagnosing purposes.
These codes are developed for the execution of the car
details to the user easily to understand the values and
strategies of the car to maintain it in the good condition.
The command for running the script:
# sudo python obd.py
Fig. 4. Output of Pi screen

978-1-5090-0774-5/16/$31.00 © 2016 IEEE
B. Execution of Node-Red Script in PI
NODE-RED is the booming IOT platform in the
present for developing the IOT applications. It provides
easy code less method of working. This makes every
person who has no idea on the connections or the way to
write the program can use the node flow easily for
understanding and creating a new node flow. But in some
cases a few line of coding will be needed in the java scripts
which will be used in the function node for development
purposes because this Node-Red was developed from the
Node js scripting language for better usage.
a) Implemening NODE-RED in Raspberry Pi
Here the NODE-RED is installed in the same
raspberry pi which we were using for the OBD output display
this node-red is installed with the pre installation of Nodejs
which is a background working platform for node-red. This
node-red works with the browser which can be used with the
machine address to run the flow.
In Terminal:
# sudo npm install –g node-red
# node-red
In Browser:
# http://machine address (ip address):1880 for
distance user.
# http://localhost:1880 for local host user.
b) Flow Diagram of NODE-RED in Raspberry Pi
The flow diagram is done easily by connecting the
node present in the browser terminal which is shown in Fig. 5
Here the pulse sensor which was connected to the GPIO pins
of the raspberry pi are configured with the GPIO node present
in the browser by the IP address this can be configures the
machine which was connected and a function node is placed
for a basic loop to check the variation in the pulse value which
indicates high pressure or low pressure. i.e. (120/80mm Hg)
[3]. This suddenly indicates the variation in value to the
Twilio app which is used by the user’s emergency contacts
which was predefined in the node.
Fig. 5. Node Flow in NODE-RED
V. FUTURE WORK
These steps will be done for the future work:
 Now only a sample text message is sent to the
emergency contact which will be not helpful. So, the
GPS co-ordinates can be collected by connecting the
Global Positioning Device to the Raspberry Pi which
will be a better way to get fast recovery step before
the condition goes worse.
 Instead of using the screen to check the details and
condition of the car if an app [4] is developed
through the pi the user can see the details of the car
from any place without having touch with the car, so,
it will be useful for the number of car holders and
travel services to identify the position and condition
of the car.
 Then a logger can also be designed to develop the
data log about the details of the functioning of car
engine and parts for maintenance purposes.
 The node-red provides many IOT application based
node like IBM Watson, blue mix, IOT push. This can
be used for cloud communication [6].
VI. CONCLUSION
This paper discuss the way to develop the OBD-II self-
diagnosing tools for the domestic purpose and to use the tools
for reducing the maintenance cost and increase in the
condition of the car by the user and the second part deals with
the maintenance of the user or driver who drives the car. If any
abnormality occurs while driving an emergency message will
be sent to the concerned safety contact to get counter measure
to avoid causalities. This will lead to advancement in the
automobile and health care technologies.
ACKNOWLEDGMENT
We thank C-DAC for providing support and allow us
to work on our project in their R&D center. We also thank our
ECE Department of Vel Tech University, Chennai and C-
DAC, Pune for allowing us to work and support.
REFERENCES
[1] Jian Hu, Gangyan Li, "City-Bus Network Control System and Its Key
Technologies in Development", in Proceedings of the 2006 IEEE
International Conference on Mechatronics and Automation, Luoyang,
China, pp.2312-2317, 2006.
[2] Engr. Leonard U. Ambata, Marc Carlo E. Lijauco, Christian Angelo C.
Nuval , Richard Justin V. Vergara, “Distance Monitoring Vision System
for Automobiles using Image Processing,” 8th IEEE International
Conference Humanoid, Nanotechnology, Information Techonology
Communication and Control, Environment and Management
(HNICEM).
[3] http://www.heart.org/HEARTORG/Conditions/HighBloodPressure/AboutH
ighBloodPressure/Blood-Pressure-vs-Heart-Rate UCM_301804_ Article . j
sp#.VvolZNJ97cs
[4] Oscar Alvear, Carlos T. Calafate, Juan-Carlos Cano, Pietro Manzoni,
“Validation of a Vehicle Emulation Platform Supporting OBD-II
Communications,” 12th Annual IEEE Consumer Communications and
Networking Conference (CCNC),2015.
[5] Jheng-Syu Jhou, Shi-Huang Chen, Wu-Der Tsay, Mei-Chiao Lai, “The
Implementation of OBD-II Vehicle Diagnosis System Integrated with
Cloud Computation Technology,” Second International Conference on
Robot, Vision and Signal Processing,2013.
[6] IBM, “Node-red,” http://nodered.org/.

202_camera ready_RTEICT_16_prasanth (1)

More Related Content

What's hot (20)

Similar to 202_camera ready_RTEICT_16_prasanth (1) (20)

202_camera ready_RTEICT_16_prasanth (1)