HOME AUTOMATION THROUGH WEB BASED
MOBILE DEVICE USING RASPBERRY PI R.Sathyaraj1, R.Shanmugapriya2, K.Shanmugapriya3, S.Shobika4, S.Sindhuja5
Assistant Professor1, U.G Student2,3,4,5
Department of Electronics and Communication,
Kings College of Engineering, Punalkulam, Pudukottai.
Abstract— Home automation web based mobile device
project will be able to design and implement automatic
intruder sensing and alerting system using raspberry pi 3
based video acquisition system. For an effective Human
Computer Intelligent Interaction, we integrate Raspberry pi
based real-time security that needs to recognize the motion in
unauthorized area. Here an efficient Scale-invariant feature
transform (SIFT) combined with optical flow algorithm. If
any abnormal condition exists then it will send an image to
relevant person via WhatsApp.
Index Terms—Frame separation, Intruder Detection,
Training, Alerting (key words).
I. INTRODUCTION
Motion detection is an important security operation in the
selection of significant segments of the video signals. The
ongoing research on object tracking in video sequences has
attracted many researchers. Detecting the objects in the video
and tracking its motion to identify its characteristics has been
merging as a demanding research area in the domain of image
processing and computer vision.
An image capture system with python computing can
extract information from images without need for an external
processing unit, and interface devices used to make results
available to other devices. The choosing of a python platform
is very unique and easy to implement.
Considering the requirements of image capturing and
recognition algorithm, Raspberry Pi processing module and its
peripherals, implementing based on this platform, finally
actualized Image Capturing using Raspberry Pi system
(ICSRS). Experimental results show that the designed system
is fast enough to run the image capturing, recognition
algorithm, and the data stream can flow smoothly between the
camera and the Raspberry Pi board.
By receiving alerts on your device the user are informed of all
possible issues occurring in the house and it gives them
various possibilities to deal with the problems. This is how an
automated system proves useful to people in providing them
security, comfort and easily accessible.
II. EXISTING SYSTEM
A. Closed Circuit Television
Closed circuit televisions are also known as CCTV. These
systems are the most commonly used security system. CCTV
cameras record live videos or capture images. Two kind of
CCTV available are wireless and wired. These systems are
capable of recording live videos for a time period. CCTV
cameras can be applied anywhere but it is most commonly
used for security purposes in banks, airports, shopping centers
etc. CCTV cameras continuously monitor a particular place or
sometimes operated for a particular event. The earliest CCTV
systems were not capable of recording and storing
information. It was the development of reel-to-reel media
which became crucial turning point in the enhancement of
modern systems. These systems are highly influential in crime
prevention, industrial processes, traffic monitoring etc. Digital
Multiplexing allows several CCTV cameras to record at once.
These enable the recording events at various locations. The
latest CCTV systems enhanced its performance by coupling
with Internet. Industrial processes that take place under
conditions dangerous for humans are today often monitored
with CCTV systems. Chemical Industry and Nuclear Industry
are the examples of industries in which these systems
supervise and provide a highly beneficial device.
B. Home Alarm
Security alarm is a system designed to detect intrusion and
unauthorized entry into a building or area. These systems are
used in residential, commercial, Industrial and military
properties for protection against burglary or property damage,
as well as personal protection against intruders. Some alarm
system serves a single purpose burglary protection; the
combination system provide both fire and intrusion protection.
Systems range from small self-contained noisemakers, to com
plicate d, multi-area systems with computer monitoring and
control. Alarms comes with different of sensors such as
Passive Infrared Detectors (PIR), Ultra Sonic Detectors,
Microwave detectors, photoelectric beams, glass-break
detection, vibration or inertia detectors and so on.
III. PROPOSED SYSTEM
Block Diagram
Final frame
Video to frame
conversion
Camera
Opencv
Library
alert
Rasbian OS
Power Unit
Raspberry Pi-3
With image
processing tools
Display
Monitor
Library
WIFI/LAN
Blob analysis
Threshold
matching
Frame
preprocessing
Background
subtraction
The aim of our project is to propose a raspberry pi computer
with open CV based approach to identify the moving object
detection. It allows handling scenes containing moving
backgrounds and gradual illumination variations, and achieves
robust detection for different types of videos taken with
stationary cameras. This can also be used for obtaining
detection information related to the size, location and
direction of motion of moving objects for assessment
purposes. The motion capture image is sent to the owner’s
Whatsapp when such an alarm is risen which he can view from his mobile device, anywhere and anytime.
The proposed method uses the raspberry pi board is the main
controller. The latest version of raspbian wheezy is used on to
the board.
The system designed system can be operated in two
different sessions, ie one for capturing and creating a data base
and the other session is to capture the image and which can be
used for identifying or comparing the images in the database.
Here in the second session we use methodology of face
recognition for finding the matches.
It is realized that the real-time firmness of video flow with
high reliability to detect and track the object in frame
sequence.
IV.HARDWARE REQUIREMENTS
A. Raspberry Pi:
The Raspberry Pi 3 Model B features a quad-core 64-bit
ARM Cortex A53 clocked at 1.2 GHz. This puts the Pi 3
roughly 50% faster than the Pi 2. Compared to the Pi 2, the
RAM remains the same – 1GB of LPDDR2-900 SDRAM, and
the graphics capabilities, provided by the Video Core IV GPU,
are the same as they ever were. As the leaked FCC docs will
tell you, the Pi 3 now includes on-board 802.11n WIFI and
Bluetooth 4.0. WIFI, wireless keyboards, and wireless mice
now work out of the box.
B. Hardware Specifications
SOC: Broadcom BCM2837
CPU: 4×ARMCortex-A53,1.2GHz
GPU: Broadcom Video Core IV
RAM: 1GB LPDDR2 (900 MHz)
NETWORKING: 10/100 Ethernet, 2.4GHz 802.11n wireless
BLUETOOTH: Bluetooth 4.1 Classic, Bluetooth Low Energy
STORAGE: micro SD
GPIO: 40-pin header, populated
PORTS: HDMI, 3.5mm analogue audio-video jack, 4× USB
2.0, Ethernet, Camera Serial Interface (CSI), Display Serial
Interface (DSI)
C. Raspberry Pi Camera:
The camera module used in this paper is raspberry pi camera
module as shown in the figure. The camera module plugs to
the CSI connector on the Raspberry Pi. It's able to deliver
clear 5MP resolution image, or 1080p HD video recording at
30fps. The camera module attaches to Raspberry Pi by a 15
pin Ribbon Cable, to the dedicated 15 pin MIPI Camera Serial
Interface (CSI), which was designed especially for interfacing
to cameras. The CSI bus is capable of extremely high data
rates, and it exclusively carries pixel data to the BCM2835
processor.
V.SOFTWARE REQUIREMENTS
A. Python
It is a high level programming language which allows
programmers to express the concepts in fewer lines of codes.
It provides reduction in coding lines than the programming
languages such as c and JAVA.
B. Open CV
The application written for this thesis relies heavily on
computer vision, image processing and pixel manipulation, for
which there exists an open source library named Open CV
(Open Source Computer Vision Library), consisting of more
than 2500 optimized algorithms. Uses range from facial
recognition, object identifying, classifications of human
actions in videos, achieved with filters, edge mapping, image
transformations, detailed feature analysis and more. Having
Linux support, this is the perfect choice for developing an
application specifically for a Raspberry Pi based system.
C. Whatsapp Library
Yowsup is a python library that enables you build
application which use Whatsapp service. Yowsup has been
used to create an unofficial WhatsApp client. yowsup-cli is a
command Yowsup comes with a command line client exposes
many yowsup capabilities for quick access in command line.
At the moment it supports only a smaller set of yowsup
function as it's still in under heavy development, but
eventually it will expose every single yowsup capabilities.
III. ALGORITHM USED
A. Sift (Scale Invariant Feature Transform):
It is used to identify internal character and direction of
the object. Track images, detect and identify objects(which
can be partly hidden as well).This helps uniquely identify
features. Let’s say you have 50,000 features. With this
representation, you can easily identify the feature you are
looking for (say, a particular eye or a sign board).
B. BACKGROUND SUBTRACTION
Background subtraction is the process of separating out
foreground objects from the background in a sequence of
video frames. Background subtraction is used in many
emerging video applications, such as video surveillance,
traffic monitoring, and gesture recognition for human-machine
interfaces and etc.
C. Blob Analysis
When moving object is selected by the color background
modeling its performance degrades and morphology is tracked
individually because there may be occlusion occurred. Here in
this paper group tracking is used to remove the problem of
misidentification. Grouping scheme is required to classify
moving object into several object. Blob labeling is used to
group moving object which required less computational cost
also it is easily implemented.
VI.CONCLUSION
In this paper we proposed a security system, which is able to
monitor the home perimeter and notify the owner when a
visitor intrudes. The system is able to notify the user instantly
through Whatsapp message. Unlike the existing CCTV
systems, the software of the proposed system can be updated.
It is an efficient and cost effective security solution for home
security automation. The advantage of using this system is
that, it is very user friendly and more importantly it is very
simple to operate. This system is smaller, lighter and
with lower power consumption, so it is more convenient than
the PC-based face recognition system. Apart from, this
technique is better than other home automation methods, using
SMS and DTMF as the call tariff, is a big drawback.
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