IRJET- Automation Software for Student Monitoring System

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 12 | Dec 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 779
AUTOMATION SOFTWARE FOR STUDENT MONITORING SYSTEM
Kedar Pathak1, Hrishikesh Patil2, Hrishikesh Ekawale3, Snehal Shinde4, Swati Chandurkar5
1,2,3,4Dept. of Computer Engineering, PCCOE, Maharashtra, India
5Prof. Swati Chandurkar, Dept. of Computer Engineering, PCCOE, Maharashtra, India
---------------------------------------------------------------------***----------------------------------------------------------------------
Abstract - Attendance was commonly used as a technique for
tracking the academicbehaviouroflearners. Usually, however,
standard methods are time consuming and incorrect. The
updated attendance list will then be uploaded to an online
database and can also be saved as a file for subsequent
transfer to a PC. The proposed system enables learners to
electronically monitor class attendance. The simulation uses
distinct types of techniques to define the identity card of the
student. The reader or sensor is connected to the attendance
information system in order to save all attendance data
directly to the database and can be used later to manage the
information.
Key Words: Attendance system, automation , accuracy,
sensors.
1. INTRODUCTION
Attendance plays a key role in determiningkidsand
young people's academic performance in schools and
universities. Regularparticipationindicatesthatlearners are
less likely to participate in behavior that is delinquent or
harmful. Chronic lack raises the danger of failure at college
and early dropout. Manual maintenance of attendance are
inefﬁcient due to the following reasons:
It takes away a lot of lecture hours prone to proxies
or impersonation. The aim of this research is to create a
secure attendance recording scheme based on electronic
attendance to monitor and analyse students existence. This
system can obtain and store information to monitor
attendance automatically. Teachers conduct a tinyhandheld
with a finger scanner and learners press their fingers to
record attendance. Manual data entry can be avoided no
proxy presence made. The main objective of thisprojectis to
monitor the attendance of students in lecture sessions and
laboratory and others in a more effective way. A stricter
approach especially to preventstudentscheatingabouttheir
attendance is additionally tedious, where a lecturercallsout
the individual names from the students list and validate the
presence of every single student. Such manual techniques
have been demonstrated to be hard and time consuming to
take student participation. Thus,a semi-automatedsystemis
needed to eliminate all these problems.
It is therefore our goal tocreatea mobileattendance
scheme fitted with an internet database, in particulartostop
data loss and to encourage paperless and a greener
workplace. In addition, the application will assist decrease
wasted time, resulting in increased teaching productivity in
the classroom.
2. SERVEY OF METHODOLOGIES
2.1. Face Detection:
Face recognition idea for implementing a scheme
that marks a specific person's participation by identifying
and acknowledging the face [6].
The identification of the face is based on the following
parameters:
A. Pose Estimation
There are three angles to determine the head pose:
roll, yaw, pitch. Typically all these angles range from -90to+
90. During face-log generation, theroll andpitchareadapted
by aligning method, so our only problem is the yaw angle.
The coordinates of the nose tip and also the point between
the eyebrows using face detection landmarks. If there are
such points (x1, y1) and (x2, y2), the yaw angle shall be
calculated as:
yaw= abs(arctan 2(y2 − y1, x2 − x1)) (1)
B. Sharpness
Because the faces are moving, it is very probabletohave
blurry pictures in real-timevideosequences.Soitisessential
to include this function in face quality evaluation. The
variance of a Laplacian picture to calculate the sharpness of
an picture.
Sharpness = (i,j)∈_(x,y) (_I(i, j) − _I)2 (2)
C. Image size or resolution
The position of the eye corners in a face using facial
landmark detection. Let (xL, yL) be the left eye corner
coordinates and (xR, yR) be the correct eye corner
coordinates. The distance between them is as follows:
Resolution = sqrt((xL − xR)2 + (yL yR)2) (3)
The normalized the resolution acquired with the Euclidean
distance limit as,
Normalized Resolution (NR) = Resolution / threshold (4)

D. Brightness
In real-time apps such as surveillance cameras,
changes in lighting circumstances are quite prevalent. Local
extraction of features on lighter faces is simpler to apply
than on darker faces. This function must therefore be
included in the face quality evaluation. We calculated the
mean of all the intensities of different channels (R, G, B)
current in the picture to achieve this parameter.
Brightness = (R + G + B)/3 (5)
These systems perform satisfactorily with different
facial expressions, lighting and pose of the person. There is
room for improvement since thesesystemssometimesfail to
recognize every face student present in the classroom. This
device portable for easy use even when the sessions are on,
without disturbing the class.
2.2. Voiceprint:
It is the responsibility of the voiceprint recognition
server to check the voiceprint of learners. Once a student
wishes to register his presence in the school, his identity
would be verified by the voiceprint coming. The captured
speech clip and the stored voiceprint model of the student
will be compared after the server gets a request for
recognition to determine if they are from the same
individual. If so, the message required for submission of
additional participation will be returned to the client,
otherwise the server will return a signal of failure of
verification. As well as controlling the main logic of the
attendance monitoring method, the attendance collection
server gets the presence submission. The lecture-version
app communicates with the server controlling the activity
starting and ending, while the student-version app collects
the server course list. All attendance documents are stored
by the database server. Each record contains a number of
required fields, such as student I d, course I d, and
submission time. In addition, class-related information
including lecture moment, place, and student list of this
course is also stored in the database, which connects the
attendance documents to the course,allowingthelecturer to
access the data intuitively. The data presentation server
offers access to the attendance information with all
functionalities. The server shows its featuresasa web-based
gateway. By interacting with the database, the server
receives information about the classes and participation
records of the learners, and then returns them to the web
portal. In addition to presenting raw records, the portal has
several built-in statistical methods,andresultsaredisplayed
through interactive plots on the page. Finally, the portal
could also export and download attendance information.
Fig. Voiceprint activity diagram
Radio Frequency Identification (RFID) is one of the
wireless technology used as an identification to detect
electromagnetic signals. For reading RFID tag information,
the RFID reader is used. There are different frequencies for
different distance that we can use respectively.
Electromagnetic wave is used to transfer the unique data
inside the tag to the reader.
The tag is activated by the electromagneticwave,so
that the unique data inside can be read by the RFID reader
[8].
In this work, we have studied an automated
attendance tracking system Students complete the
attendance taking procedure on their smartphones in
parallel. Collaboratively veriﬁcation by integrating
voiceprint biometrics withreal timelocationcouldmaximise
the accuracy of the result collected by the system.
3.3. Android based system:
Developed attendance systems that need to be
equipped with either a computer or RFID reader, leading in
extra hardware costs and maintenance. Once mounted, this
application can be used to download the list oflearnersfrom
a specified internet server. Thesystem will thenfunction asa
scanner based on the downloaded student list to scan each
student card one by one to confirm and check the existence
of the student. The camera of the device will be used as a
sensor reading the barcode printed on the cards of the
learners. The updated participation list will then be
uploaded to an internet database and can also be saved as a
file to be subsequently transmitted to a PC[5].

Fig. System architectural diagram
A. Hardware Architecture
A computer to run the internet database server and
a camera device that supports Android 2.2 or greater
versions to run the client application is the basic
requirement to deploy the system. Another optional
requirement for retrieving the attendance list file is a
personal computer.
B. System Implementation
The project's development work comprises of two
components, which are the internet database server
development and the Android application itself. The design
work involves designing the Graphical User Interface (GUI)
required to display data, capture user inputs, and integrate
with the Zxing barcode scanner, in particular to promote
barcode scanning. This attendance management scheme
utilizes the unique identification number of the student,
which for attendance validation purposes is captured from
the scanned barcode.
The ZXing library, which is incorporated into the
implementation, supports the barcode scanning process.
Basic SQL understandingisrequiredtobuildandmanage the
internet database.Theinternetserverapplication beingused
is the Xampp server, one of the parts of which is the MySQL
database.
Fig . Flow of development activities
As for the client side, the SQLite library is used to
manage a local database running on the Android device, i.e.
used to store the student list downloaded and updated.
2.4. Fingerprint Sensor:
Automatic Finger Print IdentificationSystem(AFIS)
compares fingerprints based on their ridge ending and
bifurcation differences and similarities.
If the database is too big, the effectiveness will be
reduced [3]. Biometric technology is an efficient instrument
for identity verification and fraud detection. UsingMicrosoft
Visual Basic Studio, students will be presented on a
computer teacher with more attractive and graphics and
embedded with the Fingerprint reader [4].

A. System Setup
The tool has been created an tested in smartphones
on the Android platform. The user's identity is confirmed
using the device's front camera face recognition. The
instrument uses inertial sensors on the devicetopromptthe
user to raise and hold the device at eye level (selfie style) to
initiate the recognition of the face. The RSSI values have
been stored on a server hosted by apache tomcatina MySQL
database.
B. Student mode
The student mode scans for RSSI values for the first
time, similar to the admin mode. Using Euclidean distance
from current fingerprints, the k-N algorithm is then used to
discover the three finest fingerprint matches. The mean
error in positioning is a direct resultofthe'k'magnitude. But
one's' k' value results in higher peak errors[16]. Weselected
the‘k’ value to be three as it gave optimal results. From the
coordinates of the three locations, an average coordinate is
calculated and returned for authentication. If the coordinate
is confirmed to be within the classroom, attendance will be
approved. Otherwise, the student is prompted to try again.
3. ADVANTAGES
1. Compared with traditional paper-pen-signaturetechnique
for attendance maintenance, it proves much more reliable.
2. The automated request for attendance makes the on-
campus attendance process simpler and more organized.
3. Would decrease the time wasted at the end of the session
when verifying attendance, as the verification is fully
automated.
4. The attendance methodon campusbecamemoreeffective,
quick, paperless, and minimize the student's cheating
process by using the attendance request based on electronic
sensors.
4. CONCLUSIONS
In recording student participation, standard
techniques are still being implemented in some schools
where student names are called by teachersonebyoneor by
each student's signature to determine their presence. There
are also better techniques nowadays,i.e.relyingona scheme
to record student attendance in a semi-auto way, for
example. Systems based on RFID or biometrics.Asa solution
to current issues, such systems are totally outstanding, but
one evident drawback is the extra hardware and
maintenance costs.
Tracking the participation of learners in a class has
always been a time consuming and complicated work. The
system intended and deployed an automated tracking
system for attendance in this job. Students finish the
recognition process by taking the attendance.
There are no chances of proxies in the face recognition
system, but due to some issues such as light density,
brightness, camera, quality can not be monitored by some
student participation. Even when the sessions are on, the
mobile phone is simple to use without disturbing the class.
Collaborative verification by integrating voiceprint
biometrics with real-time location could maximize the
accuracy of the system's collected result, where several
methods have been applied to protect privacy-sensitive
biometrics data.it in noisy condition can't functioncorrectly.
This scheme has shown that an inexpensive, quick
and safe automated attendance marking scheme can be
achieved in the classroom using a smartphone and Wi-Fi
fingerprinting method incorporating a monitored RSSI
procurement processanda straightforwardk-NN algorithm.
REFERENCES
[1] Siyu Yang, You Song, Honglei Ren andXinxing Huang “An
Automated Student Attendance Tracking System Based on
Voiceprint and Location” The 11th International Conference
on Computer Science & Education (ICCSE 2016) August 23-
25, 2016. Nagoya University, Japan.
[2]. Vishal Naidu1, Kumaresan Mudliar2 and Kailas
Devadkar3 “WLAN Attendance Management System” 2017
IEEE International Conference on Smart Technologies and
Management for Computing, Communication, Controls,
Energy and Materials (ICSTM),Veltech Dr.RR & Dr.SR
University, Chennai, T.N., India. 2 - 4 August 2017.3-6.
[3]T.W. Lim, M. Moghavvemi*“CapacitiveFingerprintSensor
Chip for Automatic Matching”Dept.ofElectrical Engineering,
Faculty of Engineering, University of Malaya, 50603 Kuala
Lumpur, Malaysia.
[4]M.A. Meor Said, M.H. Misran, M.A. Othman, M.M. Ismail,
H.A. Sulaiman, A. Salleh, N. Yusop “BIOMETRIC
ATTENDANCE” 2014 International Symposium on
Technology Management and Emerging
Technologies(ISTMET 2014),may
27,29,2014,Bandung,Indonesia.
[5]Siti Aisah Mohd Noor, Norliza Zaini, Mohd Fuad Abdul
Latip, Nabilah Hamzah “Android-based Attendance
Management System” The 11th International Conferenceon
Computer Science & Education (ICCSE 2016) August 23-25,
2016. Nagoya University, Japan.
[6]Shubhobrata Bhattacharya, Gowtham Sandeep Nainala,
Prosenjit Das and Aurobinda Routray “Smart Attendance
Monitoring System (SAMS): A Face Recognition based
Attendance System for Classroom Environment” 2018 IEEE

18th International Conference on Advanced Learning
Technologies.
[7] Anand S, Kamal Bijlani, Sheeja Suresh, Praphul P
“Attendance monitoring in classroom usingsmartphone &
Wi-Fi fingerprinting” 2016 IEEE 8th International
Conference on Technology for Education.
[8]Dania Eridani and Eko Didik Widianto “Simulation of
Attendance Application on Campus based on RFID (Radio
Frequency Identifiation)” Proc. of 2015 2nd Int. Conference
on Information Technology, Computer and Electrical
Engineering (ICITACEE), Indonesia, Oct 16-18th.

IRJET- Automation Software for Student Monitoring System

More Related Content

What's hot (20)

Similar to IRJET- Automation Software for Student Monitoring System (20)

More from IRJET Journal (20)

Recently uploaded (20)

IRJET- Automation Software for Student Monitoring System