In larger classroom environments, instructors can have trouble singling out students suffering from physical ailments, students without adequate sleep, or students blatantly abusing the classroom environment (pulling out phones during class, etc.). Technology can alleviate the teacher's burden of monitoring these factors so they can focus more on delivering their lessons.
What it does
The project scans faces and determines attributes like emotional state.
How we built it
We used the Python programming language with Flask for the bulk of the project. The Face API from Microsoft's Cognitive services allowed us to scan faces and receive information about them.
Challenges we ran into
The time constraint was rough, and most of the team barely got sleep the Friday night before the event.
Accomplishments that we're proud of
The team managed the project with about 4 hours of sleep each.
What we learned
We tried out a few technologies like sqlite, Dynamo DB, and Firebase if we didn't get around to them or decided they weren't suitable for our project or time constraint.
What's next for Student Emotion Monitor
We want to implement live camera snapshots and integrate a robust database with the project.