LEARNING MANAGEMENT SYSTEM WITH AI PROCTORING

In this Learning Management System (LMS) project, the MERN stack (MongoDB, Express, React, Node.js) is integrated with machine learning to create a secure platform for students, instructors, and administrators. MongoDB stores student data, including facial images for authentication during exams. Express manages API requests for real-time face verification. React provides an interactive interface for students to participate in exams while their faces are captured. Node.js executes machine learning models to authenticate students by comparing real-time facial data with stored images, ensuring exam integrity. The system also tracks student engagement by analyzing gaze patterns, ensuring students stay focused and are not using unauthorized aids. This ensures fairness and security in online exams, maintaining academic integrity. The use of machine learning enhances authentication and detects suspicious activity during exams. The system fosters a trustworthy academic environment by preventing academic dishonesty. Multi-Modal Learning (MML) is used for enhanced face identification and behavior monitoring. It combines facial images and gaze patterns to track student movements during exams. The system detects when a student turns away or engages in suspicious behavior, such as excessive looking around, which may indicate cheating. MML ensures students remain focused on the exam content and not external resources, improving the overall examination process and promoting academic integrity. 

    Keywords: Learning Management System (LMS), MERN Stack, Machine learning, Facial Recognition, Online  Exam security, Admin, Instructor, Student, Face Authentication