Online Examination System using Raspberry Pi

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 Online Examination using Raspberry Pi


Online Examination using Raspberry Pi – Nowadays  online  exam  has  been  used  by  most institutions,  organizations,  schools  and  colleges  for  conducting exams.    The  most  commonly  used   online  examination  system is conducted  by  giving  user  id  and  password  for  candidates  and then  logging  into  the  current  web  page  and  answering  the questions.  It has lot of bugs and anyone can misuse the password and anyone  can  malpractice  in the exam.  Thus  a  need  of secure system  is  required.  In  this  project  we  use  an  enhanced  model raspberry  pi  3.  Also  we  use  webcam  for  capturing  the  image which  captures  the image when  it  detects any motion  by   using the Passive Infrared  Sensor  (PIR)and the captured image is sent to  the  raspberry pi  for face  detection  with the  help of  openCV.  Then, the face  detected  is  compared  with  the  database,  to check whether face  detected  is  applied  candidate  or  not ,  if  it matches then webpage on which the questions are available is opened and the  candidate  can continue  with  the  exam.   Thus,  it provides  a secured online examination system


  Nowadays,  the  online  examination  has  become  a growing trend  in    education  assessment.      It  has  been  adopted  by various  institutions,  colleges  and  schools  to  be  effectively conduct  exam.  An  online  examination  without  any authentication  is  like  unto  a  programmer  without  any knowledge  about  the  coding.    There  are  various  techniques used  for  authentication.    Even  though  there  are  different constraints  of  online  platform  and  surrounding  environment, but  they  cannot  be  entirely  relied  upon.    The  traditional username-password  is  one  such  mean  as  this.    But  the traditional  system    has  many  loopholes  as  the    student  can share  his  or  her’s  passwords  with  other  and  can  do malpractices.  Hence  to prevent  such  things we  go  for  a  more sophisticated  method  of  authentication  by  using  face detection   In  our  project we  have  done both  face  detection  and face recognition  using  raspberry  pi  3  model  which  is  a minicomputer of a credit card size  and also by using webcam.  For the real time image processing we have used Open Source computer  vision  (Open  CV) which  is  a widely  available  and advantageous  image  processing  software  tool.    In  the Advanced  Online  Examination  using  Raspberry  Pi  we  have used a  PIR  sensor    to  detect  the  motion  of a  person  turns on the webcam and we have also used a  system  which can detect as  well  as  recognize  a  person.  If  the  person  has  been recognized  the  webpage  of  the  exam  is  opened  and  he  can attend the exam and the questions are displayed from the database.






The  Secure  Online  exams  using  students  devices    makes use  of  the Learning  Management  System  (LMS)  such as  the Moodle to perform  exams.    The  examination  is  performed on student’s  laptops.  However the  student authentication is not done by using this system.   The secure online exams on thin client uses  the  Moodle  to manage the  quiz  activity.   Ubuntu  OS is fast,  free  and incredibly  easy  to use.    The  LTSP  adds  thin client  support  to  Linux  servers.



In  this  system  we are  providing  an  integrated  system  which provides  both  face  detection  as  well as  face  detection  of  the person who appears for the examination. The proposed system uses  provides  the  security  for  writing  the  examination.  The system  uses  the PIR  sensor  to  detect the  motion  of  a person and makes  the    webcam to  be  switched  ON.    The  webcam is connected  to  the cam  port of  the  Raspberry  Pi  3 model.  The Raspberry  Pi  3  is  an  advanced  model  compared  to  other Raspberry  Pi  models  with  1.2  GHz  quad  core and  wih 1GB RAM. The image is captured and with the use of haar cascade classifier  the  face  is  detected  and  is  compared  with  the database  to  recognize  it.  If  the  face  is  recognized  then  the webpage  of  the  exam  is  opened  and  the  questions  are displayed.


  1. Raspberry Pi
  2. Camera
  3. PIR sensor


This advanced online examination system can thus be created to  provide  both  face  detection  and  face  recognition.  It  is  a compact  system  and  also a  cost  effective  system  which  uses the Haar cascade classifier  for face detection with an accuracy of 92.5%.  The connection  of  the  system to  the  laptop  can  be done  by  wireless  connection  whereas in  Raspberry Pi  2  does  this by an Ethernet connection. 


The  system  can  also  be  used  for  various  other  applications such  as  for  security  in  houses,  banks,etc.  The  system  can provide a  more  efficient, compact and  a  less  cost system  that can provide both face detection and recognition.

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