Inspiration
Due to the pandemic situation, the university had to switch to online mode. Supervising online exams creates a fair exam environment for all students. To prevent deception in online exams. According to individuals, online examinations are vulnerable to cheating like doing online searches, using phones, attempt UFM during the exam. Due to excessive fraudulent activities, deserving candidates do not get rewards and recognition for hard work. This is because cheating became very normal. So a student with no knowledge gets a higher score than those who are worthy.
What it does
It allows for monitoring student's behavior during the test. The teacher will get to know whether someone is cheating or using unfair means like a mobile phone, laptop, book, etc. and if someone tab switches or use right-click or modifier keys. To tackle the problem, we have analyzed different scenarios to avoid deceptions are as follows Multiple Face Detection Tab Switching Face Not Visible Mobile Phone Detection Book Or Any Prohibited Object Detection Disable Right Click and Modifier Keys.
How we built it
Our Application will have two dashboards:- Student Dashboard, in which students can Join Exam with Code provided by their teacher. After Exam, Student can check their Results. Teachers Dashboard, in which they can create an exam and share exam code. A teacher can check the student's behavior or any Prohibited and UFM during the exams. We have tested our working prototype by giving it to our friends.
Challenges we ran into
Had very limited time to plan, develop and test the product.
Accomplishments that we're proud of
Completed our Online Exam Proctoring Application within a limited time.
What we learned
Learned a lot of things, first to work under pressure when you have limited time.
What's next for Testify
We will work to make our UI more interactive and to add some more interactive features such as light/ dark mode, question generator, and chat assistance.
Built With
- css
- express.js
- javascript
- mongodb
- mongoose
- node.js
- pug
- tensorflow

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