Examinator an AI-enabled smart online examination system which facilitates invigilators to take online exam efficiently. This system is designed and developed using MERN Stack. WebRTC is used for video conferencing modules and Machine Learning Algorithms are processing streams coming from a candidate's webcam in order to detect and classify deceptive activities and redirecting most suspected ones to the invigilator.

1. Examinator
Smart Examination System
Ahmed Pervaiz 2017042
Annas Ali 2017074
Omer Munam 2017219
Muhammad Kashif 2017287
Saif-Ur-Rehman 2017403
Supervisor: Engr. Dr Ahmar Rashid
Co-Supervisor: Engr. Dr Muhammad Hanif

2. Introduction
• Examinator is an AI enabled smart online examination system.
• Examinator facilitates instructors/invigilators to take online exam remotely.
• Examinator has user friendly interface.
• Examinator is developed to ensure less deception and high efficiency.

3. Design

4. Web Application
Features
• Home page to navigate to Instructor or Student Portal
• Login Pages for Instructor and Student
• Student/Instructor Dashboard
• Courses Page for Instructor and Students
• Schedule page for Instructor and Students
• Exam Page for Instructor and Students
• Checking if Student Leaves the Browser window
• Random selection of questions from pool.
Web Application

5. Process View
(Invigilator)
Activity Diagram

6. Process View (Students)
State Diagram

7. Physical View

8. WebRTC (Real-Time Communication)
• Instructor can create room (Exam Hall).
• Student can join room (Exam Hall)
• Instructor can view streams of all students while students can't.
• Signaling Server Setup.
• Integrating WebRTC with web application.
• Invigilator can see most suspicious students classified by AI model.
WebRTC

9. WebRTC
Activity Diagram

10. AI Model
• Facial Recognition
• Multiple People Detection
• Phone Detection
• Eyeball & Face Tracking
• Mouth Monitoring
• Pattern Recognition Model
AI Features

11. AI Demonstration
Person and Phone Detection
Mouth Opening Detection

12. AI Demonstration
Head Pose Detection
Eye Tracking

13. Technologies Used

14. References
• https://reactjs.org/docs/react-api.html
• https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6909637&tag=1
• https://www.pyimagesearch.com/2017/04/03/facial-landmarks-dlib-opencv-python/
• https://learnopencv.com/head-pose-estimation-using-opencv-and-dlib/

15. Thank You!