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Secured Electronic Voting Machine Using Biometric Technique with Unique
Identity Number and IOT
Chapter · January 2020
DOI: 10.1007/978-981-15-3172-9_31
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Secured Electronic Voting Machine Using
Biometric Technique with Unique
Identity Number and IOT
Kone Srikrishnaswetha, Sandeep Kumar and Deepika Ghai
Abstract Elections play an important role in our democratic country as people
can select a person as a leader for the government. This paper was about a new
proposed methodology having a highly secured process. This consists of mainly
Aadhar, biometric and IOT. Aadhar ID is a unique card for everyone, biometric face
recognition for security and IOT for the safe and immediate results. This proposed
system has automatic counting of votes: highly data secured system, sending of data
immediately and safe voting.
Keywords EVM · Secured components · Face recognition · Unique ID card ·
Cascade classifier technique · IOT
1 Introduction
India is a country where elections play a major part in the government. It is a method
of selecting a candidate for the government to rule [1–6]. This paper explains about
secured voting and the process of using biometric for better elections. Selecting a
candidate for the government was important, so people have trust in the electronic
voting machine as it gives the correct voting [5–12]. So the EVM should be designed
so has to be highly secured and safe. They are many technologies like polling booths,
ballots and punch cards, e-voting, block chains, using a microcontroller, network
security, i-voting, online voting, and GSM module. But still, they are many challenges
in EVM at present days [13–22]. So this paper explains a proposed methodology of
secured EVM using face recognition biometric, a unique card with IOT [15, 24–28].
Biometric face recognition is useful for the identification of people, and voter cannot
K. Srikrishnaswetha (B) · S. Kumar
Department of Electronics and Communications, Sreyas Institute of Engineering and Technology,
Hyderabad, Telangana, India
e-mail: Srikrishnaswetha24@gmail.com
S. Kumar
e-mail: er.sandeepsahratia@gmail.com
D. Ghai
School of Electrical and Electronics Engineering, Lovely Professional University, Jalandhar, India
e-mail: deepika.21507@lpu.co.in
© Springer Nature Singapore Pte Ltd. 2020
H. S. Saini et al. (eds.), Innovations in Electronics and Communication Engineering,
Lecture Notes in Networks and Systems 107,
https://doi.org/10.1007/978-981-15-3172-9_31
311
312
K. Srikrishnaswetha et al.
Fig. 1 Data for using EVM past 20 years
repeat their voting. Aadhar was the unique ID number for everyone. IOT is useful
for sending of results immediately [22, 23, 29–31].
Data for using the technology in EVM from the last 20 years in the research
community were increasing as shown in Fig. 1, and data are taken from Science
Direct.
2 Literature Analysis
See Table 1.
3 Problem Statement
According to the literature analysis, there are a few major technical problems in the
voting process. First, manually counting of vote’s process is not accurate and secure
as shown in Fig. 2 [4, 6, 21].
Second, fingerprint biometric is not safe and secured at present days due to fake
fingerprint as shown in Fig. 3. A person who does not have hands is not allowed for
voting due to this process [12, 15].
Third, missing of votes was a great loss for the voting process. In India, 2019
elections, nearly 21 billion people lost their vote and few got a chance of double
voting in few places. This happened due to the improper registration of voter’s details
and no proper ID proof of a person as shown in Fig. 4a, b.
Another problem is recounting and declaration of delay in voting. In the gap of the
voting process and results, there is a chance of hacking [7–11]. Existing machines
are not connected to the online. So the transportation also takes time after the polling
of all the phases is completed.
Secured Electronic Voting Machine Using Biometric …
313
Table 1 Comparison of literature work of voting machine
S. No.
Author name
Year
Methodology
Remarks
1
Shahzad et al. [1]
2019
EVM, blockchain,
i-voting, e-voting
This is about blockchain
which is a solution at the
polling process and
security purpose. It is
useful at the
authentication of votes
2
Salah et al. [2]
2018
IOT, Network and data
security
This paper explains about
three levels of high-, lowand intermediate-level
layers
3
Han et al. [3]
2018
Online voting, privacy
preservation, end-to-end
verification.
Here, it was about the
process of the e-voting
system
4
Karim et al. [4]
2017
Automatic calculation of
results, integrated
database, and EVM.
In this, the system is used
for smart voting. They
used fingerprint by
Arduino. Registration was
good, and it generates
SMS to the voter. It gives
high data security
5
Rahman et al. [5]
2017
EVM, Arduino and
fingerprint scanner
This is for mainly
securing purpose and to
make the process faster.
The fingerprint is used for
detecting the voter is
authorized or not
6
Kalaiselvi et al. [6]
2016
EVM, identity card and
biometric
Fingerprint and Aadhar
used for the transparent
voting process
7
Anish et al. [7]
2015
GSM module, Arm 7
Cortex
This is used for sending
and receiving results
8
Ashok et al. [8]
2014
LCD, microcontroller,
sensors
This explains the
accuracy of votes and
display of results
9
Pandey et al. [9]
2013
EVM and online process
Aadhar was for
identifying people. The
easy process online
4 Proposed Methodology
The proposed methodology consists of two steps, namely registration of voter details
and voting process, as shown in Figs. 5 and 6. The hardware components used
are Raspberry Pi3 works by using virtual network computing (VNC) viewer which
is visual desktop-sharing system of PI, webcam, buttons for voting, monitor and
connecting cable and software used was Python version 3.5 and (SSH) Secure Shell
314
(a)
K. Srikrishnaswetha et al.
(b)
Fig. 2 a Hand counting, b digital ballots
(a)
(b)
Fig. 3 a Fake fingerprint, b improper fingerprint
(a)
Fig. 4 a Voter ID, b voter ID for the same person
(b)
Secured Electronic Voting Machine Using Biometric …
315
for access to the PI terminal. From the above literature analysis, we proposed a new
methodology for counting problems, biometric, registration of voter and declaration
of results.
In the proposed methodology, the webcam with good quality is used to build a realtime face detector and achieve better accuracy. Monitor/screen is used for entering
Aadhar number, face recognition and to identifying the authorized & unauthorized
voters with automatic counting of votes. Hardware consists of monitor, voting
buttons, connecting cable and wires and webcam as shown in Fig. 7. VNC viewer
works by connecting to the server with IP address using username and password as
shown in Fig. 8.
Algorithm (Registration)
Step1
Step2
Step3
Enter ID number
Capturing of images of face
Captured successfully
Fig. 5 Registration method
Start
Enter ID
Face
Detection
Training
Storing of
trained images
316
Fig. 6 Voting process of the
proposed methodology
K. Srikrishnaswetha et al.
Start
Wro
Enter
Aadhar
Number
Unauthorized
Correct
Wro
Face
Recogni
-tion
Unauthorized
Corre
Select
candidate by
pressing on
button
Voting display
on screen
Fig. 7 Hardware setup
Result saved
& stored by
using PI
Result sent
by IOT
Secured Electronic Voting Machine Using Biometric …
317
Fig. 8 Connection with IP address
Step4 Images are stored with IDs in haarcascade path.
Step5 Successfully trained
Steps6 Registration completed
Registration of voter details: Registration was important step and is used to register
details of the voter. Figure 9 shows the entering of ID number in register process,
and Fig. 10 shows the capturing of images while registering of details, and after
that, the captured images are trained and stored in the dataset. These are used for
the voting process for face recognition. Voting process: According to the proposed
methodology, voting process consists of three steps ,i.e., entering of Aadhar, face
recognition, storing and sending of data using IOT.
(1) Entering of Aadhar: The process starts by clicking on the start button.
Immediately it displays to enter Aadhar number; if it is correct, we can go
with the next step or else the person is unauthorized.
(2) Face recognition: After entering the Aadhar number, if the person is authorized
immediately the webcam will on and face recognition starts. If the face was
matched with the registered images, then it displays authorized and the person
can go with voting by clicking on one of the voting buttons. After this, the result
will display on the screen. Face recognition works by using Haarcascade frontal
face algorithm (Fig. 11).
318
K. Srikrishnaswetha et al.
Fig. 9 Entering of ID number
Fig. 10 Results of successfully capturing of images
(3) Haarcascade frontal face algorithm: It is an object or human face detecting
algorithm in which cascade can train images from many of positive images
and negative images. Every image has 24 × 24 base windows to calculate
features. Haarcascade identifies features with rectangular boxes; white indicates
the lighter position and black indicates darker positions. Integral images are that
which can calculate the images pixel values at origin (x, y) and can calculate by
adding of all image pixel values of the present pixel. How the pixel calculation
is carried out is explained below:
Secured Electronic Voting Machine Using Biometric …
319
Fig. 11 Storing and training of images
6
3
2
8
5
3
9
1
2
1
1
6
0
5
8
4
3
6
5
7
5
3
1
7
3
The first table is the numerical values from the image of the left side.
9 + 1 + 2 + 6 + 0 + 5 + 3 + 6 + 5 = 37; 37/9 = 4.11
It requires nine operations. 100 * 9 = 900.
1
7
13
21
22
7
20
25
35
15
36
40
55
72
23
46
56
76
111
24
48
60
79
107
41
The second table is the integral image values of the left side.
(76 − 20) − (24 − 5) = 37; 37/9 = 4.11
It requires four operations. 56 + 100 * 4 = 456 (operations)
The image can be reduced by using this integral image. By converting a large image
into small, accuracy increases. The rectangular frame on the image is calculated by
(x, y) coordinates, width and height of the frame.
[Y : y + h, X : x + w]
320
K. Srikrishnaswetha et al.
Algorithm (IOT)
Step1
Step2
Step3
Step4
Step5
After voting process, the data is stored in Raspberry Pi in Excel format
Data are sent to the main location through e-mail.
If else, data can be checked in Raspberry Pi by the authorized person.
It can be send manually also.
Results are released without delay.
Algorithm (Voting Process)
Step1
Step2
Step3
Step4
Enter Aadhar ID number
Immediately opening of webcam.
Capturing of live face and recognizing
Display of authorized or an unauthorized by matching the trained
images and live data.
Step5 Selecting of voting button
Step6 Voting done successfully if authorized.
Step7 Display of results.
Storing and sending of data using IOT: By using IOT, data of result are stored and
immediately sent to the office through mail. By this, late declaration of results can
be avoided.
5 Result
Experimental results is performed in three categories, i.e., authorized, unauthorized
and face spoofing as shown in Figs. 12, 13, 14, 15, 16 and 17.
1. Authorized
The process starts with entering Aadhar number as shown in Fig. 12. If the number
entered was correct, then immediately face recognition starts. If the person was
authorized, he/she can go with voting process as shown in Fig. 13. Finally, votes are
stored in excel format as in Fig. 14, and the result was sent through a mail immediately
after voting as shown in Fig. 15.
2. Unauthorized person as shown in Fig. 16.
3. Figure 17 proved that images are not detectable; only live detection was possible
in this methodology. In the process, if a person was unauthorized, then he/she
was not eligible for voting, and even though they click on voting button, it does
not take the vote as shown in Fig. 16.
Secured Electronic Voting Machine Using Biometric …
Fig. 12 Enter Aadhar ID
Fig. 13 Display of authorized and voting
321
322
K. Srikrishnaswetha et al.
Fig. 14 Result stored in Excel format
Finally, the proposed methodology works better than the existing technology for
the identification of a human face. The results are shown in Table 2.
Accuracy = 100 ∗ ((TP + TN)/N)
(FAR) = TP/(TP + FN)
(FRR) = TP/(TP + FP)
From the above comparison, we can say that our proposed methodology was better
in accuracy, and it reduces error percentage.
6 Conclusions
In our country still, the process of elections is not secured. This paper proposed a
highly secured process for fair voting. This proposed method can go with automatic
counting of votes, face recognition, better registration process, storing and sending
of results and declaration of results. So, by this, we can avoid duplicate voting, wrong
registration, fake biometric and late declaration of results for the better elections for
the better country.
Secured Electronic Voting Machine Using Biometric …
Fig. 15 Receiving of mail
323
324
Fig. 16 Unauthorized person
Fig. 17 Images cannot be detectable
K. Srikrishnaswetha et al.
Secured Electronic Voting Machine Using Biometric …
325
Table 2 Comparison of different techniques parameters
S. no.
Method
Accuracy %
Error %
FAR (precision) %
FRR (recall) %
1
Skin + edge
66.2
33.78
19.8
–
2
E + skin + edge
82.7
17.2
22.8
–
3
RGB
69
–
43.05
–
4
RGB + CBCR
77
–
36.14
–
5
RGB + H
83.5
–
33.82
–
6
RGB + H +
CBCR
90.83
–
28.29
–
7
Proposed
96.2
3.8
0.04
0.02
Acknowledgement The authors acknowledge that the photographs/images used in this paper are
their own and approved for publishing online.
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