StudyCam

Track your study efficiency through your webcam using computer vision.

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Inspiration

Research has linked sitting for long periods of time with several health concerns (obesity, increased blood pressure/sugar, unhealthy cholesterol levels). We created this project to promote productivity and a healthy lifestyle, in addition to helping people stay focused during long study sessions.

What it does

StudyCam uses your webcam to use computer vision to keep track of various information relating to distractions, including how many times you left your study area and how long you've been studying, in addition to periodically reminding you to stretch and drink water.

How we built it

Python, OpenCV, PyQt6

  1. The user starts the program by clicking "start" on the GUI
  2. StudyCam starts to keep track of the user's face using OpenCV face detection technologies
  3. If the user leaves their study area for too long, StudyCam will keep track of information such as the number of absences.
  4. The user will also be periodically reminded to get up, move around, stretch, and drink water.
  5. Once the user finishes their study session, they will be presented with a detailed session summary.

Challenges we ran into

We had a great deal of difficulty working with OpenCV and optimizing their prebuilt models for our specific use case. Specifically, oftentimes in our project, the webcam wasn't directly viewing the front of a person's face, as people usually study with their heads facing down. We had to fine-tune the model to be able to detect the noisy data, in addition to being able to track when the person left the frame.

Accomplishments we're proud of

None of us had ever extensively used OpenCV before, or frankly, any form of computer vision, so we're proud that we were able to implement such an advanced topic into our project.

What we learned

  • How computer vision works and how to fine-tune prebuilt models for personal usage
  • How to communicate data between a front-end GUI and a back-end program

What's next?

We have a lot of ideas for future additions that we didn't have time to implement this weekend at DeltaHacks:

  1. Implement functionality into a chrome extension
  2. More detailed reports, maybe include information such as total break time
  3. More accurate face/studying detection
  4. Analyze data using MachineLearning from multiple study sessions to give user insightful data on their study habits

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