Design of face detection and recognition system monitor students during online examinations using Machine Learning algorithms
Product Description
Aim:
To ease the process of attendance during online classes and to prevent malpractice during online assessments.
Abstract:
Today’s pandemic situation has changed the way of education to students. Education system had completely undertaken by online platforms. There are many platforms that provide services to schools, colleges and other educational intuitions. In addition to the online teaching, examination also has gone online. In this online education system, it is important to monitor the students presence i.e., attendance of the students, which plays vital role in making system. Even though educational institutions have adapted to online mode which is done through online portal, it is very challenging for staffs in taking attendance for a students. With the integrated webcam in online portals we can monitor the activities of students and malpractices done by them. But the attendance of the students is quite difficult and it is done manually by staffs by just seeing who are all in the streaming video. This can be bridled by face detection and recognition techniques using KNN algorithm. With this integration we can extract a facial feature vector which is otherwise known as embeddings and train it using Python Face Recognition Library, then identify the faces of the students before entering into examination dashboard. If it is matched the attendance system auto updates the presence of the particular student and we can also find the attendance percentage of the students, which is useful in analyzing the willing percentage of the students to write the exam online.
Proposed System:
In our prototype we implement Python Face Recognition Module to train the Face Images. We use KNN algorithm to analyze the nodes in face image then marks the patterns in various images which is taken in different angles. These images get trained as models in python server. We develop a web application as our ground work to mark student’s attendance during Online Exams. We develop with AJAX Api calls java-script functions to get our response and request more responsive. The status of the application and all details of student will be stored and retrieved from MYsql Database Server which is maintained periodically. We implement JDBC connection in java Servlet to access our database. All the requests are sent to the Backend Business Logics which is written in Java Servlets using J2EE technology.
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