Web-Based Online Embedded Security System And Alertness Via Social Media

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 2767
WEB-BASED ONLINE EMBEDDED SECURITY SYSTEM AND ALERTNESS
VIA SOCIAL MEDIA
MEHARAJ BEGUM.R[1], PRIYADHARSHINI.K [2], SWATHI.K[3], ANUSHA.P.M [4], SOFIYA JENIFER.J[5]
Students[1, 2, 3], Assistant Professor[4, 5], Dept. of Electronics and Communication Engineering, Parisutham
Institute of Technology & Science, Tamil Nadu, India.
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - This paper presents about providing more
security to BANK from intruder. Now a day protecting the
BANK from the intruder became very difficult. Sofarproviding
the security, plenty of technology has been developed. These
existing technologies cannot give the security properly. So we
have introduced new technology to provide a moresecurityby
using rotatable camera.
Key Words: HMM algorithm, Raspberry pi, Optical flow,
Median filter, Kalman filter, Cmeans, Canny edge
detection, Whatsapp
1. INTRODUCTION
Security is most important in every place; without
security it leads to greater loss; especially providingsecurity
to the bank is must to save all of our money; the motivation
of this paper is to provide the better security to the bank by
using new technology with latest equipment called
Raspberrypi and it follows Hidden Markov model algorithm.
1.1 Background
The featuresandcolorsofcomputervisual detection
and vision always been an area of interest for popular
companies can invest in costly high-level technology and
machinery, but with the advent of cheap and small
sized(debit-card computers such as the Raspberry Pi has a
greater role in society. The RaspberryPimicrocomputer was
developed for the sole purpose of commercial and
academicals use. The applications of any sort of computer
vision or feature detection software in general are
numerous. Examples: people tracking at shopping mall,
surveillance systems with face recognition,helpingrobotsto
pick up objects and to navigate, are monitoring the
equipment. The idea behind this is to form a foundation of
knowledge regarding embedded systems, visual detectionof
objects and the basics of real-time image processing (or
other features), upon which it is possible to add some layers
of complexity and have to undergo further research with
which to modulate projects ranging from less cost and face
recognition or small real-time systems for simple object
detection to high complex systems such as intelligent
machines with self-learning robots with the capability of
visual feedback.
1.2 Aim of thesis
The main goal is to write a python application, with
the help of Open CV libraries, which can be used on an
embedded system, specifically a Raspberry Pi to:
 Capture the coloured blobs from web camera feed
 considering these blobs are objects, and save them
in memory to keep track of their coordinates and
other properties
 Attempt to confirm the linear and realistic
movement of these objects
 Send helpful message about these objects and its
movement continuously as datagram’s (using UDP
protocol of network sockets) to any softwarewhich
makes information requests.
1.2.1 Existing system
In current state CCTV camera is used in all places
especially in Bank for securitypurposeandCCTVcamera has
been checked to find the movement or fault in the bank.
Consider the situation like the intruder is coming to bank by
today night to steal the money and this can be detected by
tomorrow morning only and then we will be checking the
CCTV camera to find the intruder.
1.2.1.1 Disadvantage
 It fails to provide the high security
 It requires large memory space to store the images
 It fails to protect the money from the intruder.
1.2.2 Proposed system
This proposed system is to provide the proper
security to the bank by using raspberry pi kit and it follows
the HMM algorithm .web camera captures the movement of
object and send those images to thebank managerandtothe
police station via whatsapp for security alertness .and it
helps to catch the intruder before he departure from the
bank with money.

2. BLOCK DIAGRAM
Fig.1 Description of block diagram:
The block diagram consist of various components
such as web camera ,raspberrypikitanddisplaymonitorand
power unit and the process is shown in the figure 1. The
camera is to monitors the bank and captures the images of it
and these images are given as input to the video acquisition
block, this will convert the images into video format.Andthis
video is given as input to the frame separation part; this will
convert the video into number of frames and the output of
the frame separation block is given as input to the raspberry
pi kit. Here it follows one algorithm called hidden Markov
model (HMM) all theimageprocessingprocessisdonebythis
algorithm. it gets the frames and it takes the two frames at
first, in that the first frame is considered as reference image
and the second frame is called as processing image, here the
changes can be detected by cmeans, that is it compares the
two frames(reference and processing images) and finds the
changes in it ,this process is done by cmeans.
And the output of the cmeans is given as input to the
various filters .at first the noise in this image can be reduced
by median filter and output of this filter is given to the
kalman filter. This filter used to find the pixel variation by
comparing the two frames. Then this output is given to the
canny edge detection; this detectstheedgesoftheimage.And
the back ground subtraction (bgs) is used to fix thethreshold
value which can be used to detect the movement changes
when it exceeds the threshold value. And the optical flow is
used to track the movement of the object flow (direction of
movement). Thefinal detected image can send via whatsapp
for alertness. This can be done by whatsapp library which
will make communication between python language and the
high level language used in the whatsapp. And the display
monitoris connected to the raspberrypi to view the detected
image. The raspberry pi requires power unit of five volt and
2amps.and it requires LAN/WIFI connection to send the
image via whatsapp and open CV contains all the functions
related to the raspberry pi and pi kit works by rasbian OS.
2.1 Hardware used:
Raspberrypi kit, web camera, power unit
2.2 Software used:
Geany, python (language), HMM (algorithm), open CV,
whatsapp library.
3. COMPONENTS DESCRIPTION:
3.1 Raspberry Pi
Raspberry Pi is a better choice when taking into
account of relatively high performance requirements of
image processing and the equipment currently available for
image processing, are the relatively inexpensive and
powerful embedded platform. Raspberrypi has the
availability of the Pi camera module,whichcancapturehigh-
clarity video as well as snaps which are another factor for
chosen RaspberryPi and this requires a continues updating
of Raspberrypi firmwaretothelatestversion.It worksbetter
with OpenCV based applications. Even though using the
officially supported camera module, It can be accessed
through the V4L APIs and MMAL and it is accepted by the
numerous third-party libraries, It can use any USB web-
camera.
 It works by rasbian OS
 It act as micro controller as well as micro processor
 It is inbuilt with blue tooth, WIFI/LAN
 It has ARM11 processor
 It has 1gb RAM
 It can accept 32 GB memory card
3.2 Web camera
Continuous monitoring and pixel support of 16
mega pixels
3.3 video acquisition
The video capture process is to convert the analog
image into the digital image by the analog to digital
converter. Next, the chrominance is been demodulated to
produce color difference video data. It converts the images
into video format.
3.4 Background subtraction
It is used for detecting the moving objects from
the difference between the current frame and a reference
frame by fixing the threshold. It helps to fix the threshold
to track the movement.
3.5 Hidden Markov model (HMM)
In a hidden Markov model, the state is not been
directly visible, but the output whichdependentonthestate,
is visible. Hidden Markov models are especially used for the
application such as speech, gesture recognition, part-of-
speech tagging, musical score following, partial discharges
and bioinformatics. A hidden Markov model can be
considered as generalization of a mixture model where the
hidden variables are considered for observation.

3.6 Median filter
Median filtering technique often used to remove
noise from the images such noise reduction is a typical pre-
processing step to develop the resultsforfurther processing.
3.7 Fuzzy c-means
(FCM) is a data clustering technique in which a
dataset is grouped into n clusters with every data point.This
is used to compare the two images to find the changes.
3.8 Kalman filtering
It is also known as linear quadratic
estimation (LQE) filter .which is used to find the pixel
variation by comparing the reference and processing image.
The Kalman filter has variety of applicationsintechnology.A
common application is for guidance, navigation, and
control of vehicles, particularly aircraft and spacecraft.
Furthermore, the Kalman filter is a widely applied concept
in time series.
3.9 Canny edge detector
It was developed by Jhon F.Canny in 1986 it is
an edge detection operator that uses a multi-
stage algorithm to detect a wide range of edges in images.
3.10 Optical flow
It detects the motion of objects, surfaces, and edges
in a visual scene caused by the relative motion between an
observer and a scene. It is also called as scene flow. Which
detects the flow of movement.The idea of optical flow was
created by the American psychologist James J. Gibson in the
1940.
3.11 OpenCV (Open Source Computer Vision Library)
It is an open source computer vision and machine
learning software library. OpenCV was developed toprovide
a common infrastructure for computer vision applications
and to accelerate the use of machine perception in the
commercial products. It has C++, C, Python, Java and
MATLAB interfaces and supports Windows, Linux, Android
and Mac OS. It has all the functions relatedto raspberrypi kit.
Advantages
 It provides high security
 It requires very less memory space to store the
images
 Less cost
 Small in size
Applications
 Bank
 Jewellery shop
 Expensive exhibition
4. CONCLUSION
In this paper a web camera is used to detect the
movement of object by using raspberrypi kit and sending
alertness messages via whatsapp and thus provides the
perfect security.
ACKNOWLEDGEMENT
The authors are gratefullyacknowledgingthesupport extent
by the respective institute in bringing out this article.
We also thankful to faculties of Electronics and
Communication Engineering department
REFERENCES
[1] ‘Motion video sensor in the compressed domain'. SCS
Euro media Conf., Valencia, Spain, 2001.
[2] GieseandT.Poggio (2003) Neural mechanisms for the
Recognition of Biological movement sand action.
Nature Reviews Neuro science 4:179–192.
[3] “Neural Networks for 3D Motion Detection From a
Sequence of Image Frames,” Chan Lai Wan and Yip
Pak Ching, IEEE, computer Science Dept., The Chinese
University of Hong Kong, 1991.
[4] Ferster and K.D. Miller. (2000). Neural mechanisms of
orientation Selectivity in the visual cortex. Annual
Review of Neuroscience, 23:441–471.
BIOGRAPHIES
Meharaj Begum.R pursuing her B.E degree in Electronics
and Communication Engineering in Parisutham Institute of
Technology and Science.
Priyadharshini.K pursuing her B.E degree in Electronics
and Communication Engineering in Parisutham Institute of
Swathi.K pursuing her B.E degree in Electronics and
Communication Engineering in Parisutham Institute of
Anusha.P.M completed her ME in VLSI Design in Kings
College of Engineering and completed her BE in Electronics
and Communication Engineering in Periyar Maniyammai
University. She is working as Assistant Professor in
Parisutham Institute of Technology and Science.
Sofiya Jenifer.J completed her ME in VLSI Design in Kings
College of Engineering and completed her BE in Electronics
and Communication Engineering in Anjalai Ammal
Mahalingam EngineeringCollege.Sheisworkingas Assistant
Professor in Parisutham Instituteof TechnologyandScience.

Web-Based Online Embedded Security System And Alertness Via Social Media

Recommended

Recommended

More Related Content

What's hot

What's hot (19)

Similar to Web-Based Online Embedded Security System And Alertness Via Social Media

Similar to Web-Based Online Embedded Security System And Alertness Via Social Media (20)

More from IRJET Journal

More from IRJET Journal (20)

Recently uploaded

Recently uploaded (20)

Web-Based Online Embedded Security System And Alertness Via Social Media