During the pandemic, classes are mostly online, and many students get distracted by playing games, watching videos, social media, and many more.

What it does

This project help teacher in identifying if students are getting distracted during online classes. The project monitors two things: facial expression, and eye movement If the facial expression differs from normal, it means the child may be watching videos, playing games, or is on social media. If they are moving their eyes a lot, and their eyes are moving away from the screen, it implies they may be distracted.

How we built it

Programming Language: Python Frontend: Module in Python for GUIs named tkinter. Backend: OpenCv, Dlib

Challenges we ran into

Smile Detector has a specific lighting environment to work and detect the smile.

Accomplishments that we're proud of

Successfully learning opencv and dlib and how to use them in a real world context.

What we learned

OpenCV, Python, Tkinter, Time Management

What's next for Focus Meter

Integration with Microsoft Teams, Zoom, and online learning platforms. Also, detecting gaming strokes through the keyboard. Further enhancements using ML algorithms for smile and eye movement detection.

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