Automated Elephant Tracker

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International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 –
INTERNATIONAL JOURNAL OF ELECTRONICS AND
6464(Print), ISSN 0976 – 6472(Online), Volume 6, Issue 1, January (2015), pp. 17-22 © IAEME

COMMUNICATION ENGINEERING & TECHNOLOGY (IJECET)

ISSN 0976 – 6464(Print)
ISSN 0976 – 6472(Online)
Volume 6, Issue 1, January (2015), pp. 17-22
© IAEME: http://www.iaeme.com/IJECET.asp
Journal Impact Factor (2014): 7.2836 (Calculated by GISI)
www.jifactor.com

IJECET
©IAEME

AUTOMATED ELEPHANT TRACKER
Avirup Basu
Electronics and Communication engineering, Siliguri Institute of Technology, Sukna, India,
Aritro Mukherjee
Electrical engineering, Siliguri Institute of Technology, Sukna, India,

ABSTRACT
In recent days the collisions between wildlife and railway have increased causing a very vital
loss to the fauna. There have been huge numbers of deaths of elephants while crossing the railway
tracks and the deaths have increased in the recent days and it has caused a serious problem. The main
cause of death is there are no early warning systems which can give an early information regarding
their location. Thus our main objective will be to provide an early warning system to the railway
department so they can act accordingly. Our automated elephant tracker is a system developed with a
motive of saving this elephants and to provide an early warning regarding their location. It consists
of a manual bot capable of running on rough terrains. It tracks a fixed area but at the same time can
also be manually controlled according to the circumstances. It has a wireless camera mounted on it
which leads visualization of the elephants and provides early information to the base station
regarding the locations and detections of this elephants. The main job of the base station is to control
our elephant tracker and at the same time to process the signal to detect the location of elephant.
Accordingly it sends the information to the railway authorities to take according steps. Which can
minimize the collision and ensure the safety of the elephants and railway system
.
Keywords: Aforge, Arduino, C#, Euclidean, WPF.
1. INTRODUCTION
Automated elephant tracker is a system developed with the motive to save elephants from
deaths by speeding trains. The system is developed by incorporating 3 major systems.
1.1: Manual + Autonomous bot
A manual bot named Black etrack v1.0.0.1 will compose the first major part of the system.
The manual bot can move through rugged terrains near a railway track. It has two modes of
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International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 –
6464(Print), ISSN 0976 – 6472(Online), Volume 6, Issue 1, January (2015), pp. 17-22 © IAEME

operation. Manual and automatic. The BET gets it power from a series of four 9V batteries. It attains
mobility through 4 wide wheels. It receives signal from the base station and it transmits the signal to
the base station by a wireless camera. The bot gets recharged from jumper stations (Charging points)
at regular intervals.
1.2: Wireless A/V camera
A wireless A/V camera is used to transfer the image from the field to the Base Station. The
wireless camera captures the image and then it send it to the Base Station by the transmitter. The
camera is relatively of 5x5 sq. cms.
1.3: Base Station
A Base station is the key part to the system. The base station performs the set of tasks
mentioned below in a hierarchal way.
1. Control the BET.
2. Receive the signal in video format from the camera
3. Process the video such that it can detect elephants using colour recognition and size
recognition.
4. If detected send a signal to the train drivers to slow down.
2. FACTS AND FIGURES OF ELEPHANT DEATHS CAUSED BY SPEEDING TRAINS
2.1: Deadly Tracks
The 21st century has seen a rapid growth of population like never before. India, the second
largest populated country in the world, in particular has seen a rise in demand regarding economical
and quick transportation systems. India's railway network being among the biggest in the world, is
constantly spreading itself in order to increase the connectivity between remote locations thus,
fulfilling the requirement of the teeming millions. But, while doing so, most of us fail to realize its
impact on the biota. We fail to realize that we aren't alone on this planet & that there are millions of
other species trying to make their living along with us. Instead of sharing our bread with them, we
tend to be ignorant about them and are always on the run to prove ourselves as the most intelligent
species on the planet. As a result of our in-human behaviour, these poor creatures (both big & small);
hardly able to decipher the complexities of human nature, have to pay a heavy price, which may
sometimes lead to their own death. With reference to the state's affidavit (state of West Bengal) there
have been, 57 elephants have died in train hits in the past 19 years. In spite of repeated warnings and
law enforcements, the railways have failed to prevent loss of lives in the elephant corridors, which is
quite evident from the statistical data we see.
2.2: An excerpt from national daily, The Telegraph, 14th November, 2013
A railway official today said that, the Jaipur-KamakhyaKabiguru Express, which mowed
down five elephants in the Chapramari forest, was running at 80-100kmph, which is double or more
the speed allowed when trains travel through forests. Since 2002, when the railway tracks between
Siliguri Junction and Alipurduar were converted to broad gauge, 40 elephants have died in train
accidents. A study by the WWF shows that most of the Human Elephant conflict occurs in the forest
border areas. So our main area of concentration are the forest border areas.
3. HARDWARE MODULE
The hardware of this system mainly consists of the bot. The bot is the main field player. It
can be manually (remotely) controlled or automatically controlled. Based on it, the hardware inside
the bot consists of the following parts.
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International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 –
6464(Print), ISSN 0976 – 6472(Online), Volume 6, Issue 1, January (2015), pp. 17-22 © IAEME

Table 1: Parts List
Si No
1
2
4
5
6
8
9

Name

Specifications

12V High Torque DC Geared Motor
300RPM
Dual DC motor Driver
Wireless, A/V camera
Arduino Leonardo
RF 2.4Ghz Serial link
RF 2.4Ghz USB link
Wheels

300 RPM, High Torque
Dual motor Driver 20A
2.2Ghz
Headers included
2.4Ghz
2.4Ghz
2cm width 10 cm diameter

Quantity
4
2
1
1
1
1
4

The bot is controlled by RF network operating in 2.5 GHz frequency range. The robot is built
on an open source multipurpose chassis. The chassis contains spots for 6 motors, 1 castor wheel, 1
line sensor array, and being an open source, it can be fitted with almost any type of components. The
BET is driven by a 4 wheel drive and it follows a differential drive steering system. The differential
drive steering system works on the principal of difference of motor speeds.
4. SOFTWARE MODULE
The software is mainly divided into two units. The first unit comprises the controlling unit
while the later comprises of the processing unit which deals with the image processing part.
4.1: Black e Track controller
The Black e Track controller is the controlling unit of the bot. It sends control to the BET by
serial port communication using a RF network of 2.4GHz. The signal on the other hand is interpreted
by the receiver and the serial data is transferred to the Arduino Leonardo Board. The Arduino
Leonardo Board sends the signal to the motor driver circuit to perform the desired operation. The
Black e Track controller has 15 buttons.
Si no

Name of the
control

1
2
3
4
5
6
7
8
9
10

Front_fast
Back_fast
Right_fast
Left_fast
Stop
Front_slow
Back_slow
Right_slow
Left_slow
Connect

11

Disconnect

12

360 deg right

13
14

360 deg left
Press to activate
keyboard controls
Activate

15

Corresponding control reflected in BET
Makes the BET move forward at maximum speed
Makes the BET move backward at maximum speed
Makes the BET turn right at maximum speed
Makes the BET turn left at maximum speed
Makes the BET stop
Makes the BET move forward at 60% of its original speed
Makes the BET move backward at 60% of its original speed
Makes the BET turn right at 65% of its original speed
Makes the BET turn left 65% of its original speed
Once you click the connect button, the controller will be connected to the
wireless communicator’s USB link
Once you click the connect button, the controller will be disconnected to the
wireless communicator’s USB link
Makes the BET turn right continuously until and unless the stop button is
pressed
Makes the BET turn left continuously until and unless the stop button is pressed
This special control is used to shift the control of BET from a pointing input
device to a Keyboard.
This is a unique security button. The password that is entered just above the
button is the activation code for the entire controller. Once entered, the user has
to press the Activate button to activate the controls

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International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 –
6464(Print), ISSN 0976 – 6472(Online), Volume 6, Issue 1, January (2015), pp. 17-22 © IAEME

The Black e Track Controller v1.0.0.1 is developed in Visual Studio 2013 using .NET
framework v 4.5.1 in C# and xaml. It contains a status box where the current command is displayed.
There are 3 progress bars. When the progress bar is in the intermediate stage, the corresponding set
of commands is executed. In the controller, the “Press to activate keyboard controls” button activates
the keyboard commands. The keyboard commands are mentioned in a tabular format below.
Si No
1
2
3
4
5
6
7
8

Keyboard keys

Commands executed

W
A
S
D
Numpad 8
Numpad 2
Numpad 4
Numpad 6

Fast forward
Fast left turn
Fast backward
Fast right turn
Slow forward
Slow Backward
Slow left turn
Slow right turn

Another button named “Activate” button is a special purpose security button. A field exist
where you need to enter the password. By default the password is “12345”. Unless you press the
activate button after entering the password, all the controls go in the disabled stage. Only after
entering the password and pressing the activate button, the controls can be enabled.

Fig 1: Screenshot of Black e Track Controller V2.0
4.2: Elephant detection system
The Elephant detection system processor is the core component of the system. The EIDS
receives signal from an on-board A/V wireless camera operating in 1-2 GHz frequency range. The
signal is received by a receiver capable of interfacing various signals of varying signal range. The
EIDS processor processes the image received to detect elephants. We have used a simple algorithm
completely based on image color and image size to detect elephants. The algorithm utilizes an image
processing [1] library called Aforge.NET [2]. The algorithm utilises two main classes. The first one
is the Euclidean color extractor class and the second is the Blob class.
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International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 –
6464(Print), ISSN 0976 – 6472(Online), Volume 6, Issue 1, January (2015), pp. 17-22 © IAEME

Euclidean color extractor filter: This filter is available in Aforge.NET framework. This filter
utilises two major parameters to extract a certain color. The parameters includes the RGB values for
the filters base color and the other parameter includes the size in pixels around the centre color. The
filter filters pixels, which color is inside/outside of RGB sphere with specified centre and radius - it
keeps pixels with colors inside/outside of the specified sphere and fills the rest with specified color.
The filter accepts 24 and 32 bpp color images for processing.

Fig 2: Image before applying the filter. Picture curtsey: www.aforgenet.com
On the above image as shown in Illustration 3, we apply the Euclidean Colouring filter with
the centre color is of 215, 30, 30 values of Red, Green, Blue respectively and a colour sphere radius
of 100 pixels. After applying the filter, we get the image as shown in Fig 3.

Fig 3: Image after applying the filer. Note: only the areas with red color remains. Picture curtsey:
www.aforgenet.com
Thus from the illustration 3, it is clear that the centre part of the rose image is filtered out. In
the case of EIDS, the centre color is roughly the average color of an elephant. In the EIDS system, an
option exist for the change of the centre color but it isn’t there in EIDS v1.0.0.1 It will be available
under v1.0.0.2. Please note that the Euclidean colouring filter is probably one of the most basic way
to approach the detection of elephants.
Blob class filter: The use of the blob class is simply to highlight the extracted region
extracted by the Euclidean colouring filter. In EIDS v1.0.0.1, there is an added facility where if a
blob is displayed in the source image, then the word “DETECTED” is also displayed in red colour
over the button right corner of the source image.
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International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 –
6464(Print), ISSN 0976 – 6472(Online), Volume 6, Issue 1, January (2015), pp. 17-22 © IAEME

Fig 4: Screenshot of the EIDS processor v1.0.0.1.
5: FUTURE SCOPE
The Black e Track works well as a surveillance robot. The camera attached with the BET is
digitally processed to detect elephants. Not only in elephant tracking, but also in other applications
including military and other places where remotely operated vehicles are required. The BET can also
be used in inspection of tunnels, pipelines and other potentially dangerous places for humans. Since
BET uses an open source Arduino board, the BET can be re-programmed to perform other
autonomous + manual jobs as well. Work is being carried out to convert the BET into a robot that
can be wirelessly charged. To increase the flexibility of charging, the future version of BET will be
incorporated with thin layer solar panel. The BET will have the capability to perform in both
“automated” and “manual” modes of operation. Lots of security protocols are to be incorporated in
the control unit of the Black e Track. We will also improve the EIDS processor to improve faster and
accurate detection.
REFERENCES
Books
1.
Digital Image Processing, Rafael C.Gonzalez, Richard E.Woods, and ISBN: 81-7808-629-8
2.
Chandramouli.H, Dr. Somashekhar C Desai, K S Jagadeesh and Kashyap D Dhruve,
“Elephant Swarm Optimization for Wireless Sensor Networks –A Cross Layer Mechanism”
International journal of Computer Engineering & Technology (IJCET), Volume 4, Issue 2,
2013, pp. 45 - 60, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.
3.
M.M.Kodabagi and Shridevi.B.Kembhavi, “Recognition of Basic Kannada Characters In
Scene Images Using Euclidean Distance Classifier” International journal of Computer
Engineering & Technology (IJCET), Volume 4, Issue 2, 2013, pp. 632 - 641, ISSN Print:
0976 – 6367, ISSN Online: 0976 – 6375.
4.
Manish P. Pujara, Lav Kumar and Ashish Mogra, “Two Phase Flow Void Fraction
Measurement Using Image Processing Technique” International Journal of Mechanical
Engineering & Technology (IJMET), Volume 4, Issue 3, 2013, pp. 130 - 135, ISSN Print:
0976 – 6340, ISSN Online: 0976 – 6359.

5.

Websites
http://www.aforgenet.com.
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