Project Info

Slouching Slugs

Devpost

This project did not submit a demo video on Devpost.

Inspiration

As STEM students, we spend countless hours hunched over screens, often ignoring our posture until the pain kicks in. Yet, we easily notice when others slouch! We realized that if we had a real-time reminder to sit straight, we could prevent long-term damage. That’s why we built Slouching Slugs—an AI-powered posture guard that nudges you before bad habits occur.

What it does

We utilize the built-in webcam or an external one and send a live feed to our program that detects if the user is slouching or not, and if so, a notification is sent to the user's desktop as well as a pop-up with advice on how they can improve

How we built it

We engineered Slouching Slugs entirely in Python, using OpenCV for real-time webcam processing and MediaPipe to track critical posture landmarks (shoulders, nose, eyes). Our system implements a 200-frame image buffer that analyzes posture state across multiple frames - only triggering Gemini API feedback when 75% of buffered frames (150+ images) confirm slouching, preventing false alarms. After generating personalized corrective advice (e.g., "Ensure your monitor is at eye level to avoid hunching over"), the deque automatically clears to avoid notification spam. The frontend delivers these insights through a Tkinter GUI and subprocess-powered desktop alerts, creating a seamless feedback loop.

Challenges we ran into

One challenge we encountered was adjusting the sensitivity of the slouch detector; at times, it was too sensitive, and a slight movement would cause it to send a notification.

Accomplishments we're proud of

We are most proud of being able to fully commit ourselves to this project and achieve what we have done today through 48 hours of coding, debugging, learning, and collaboration. This was our first hackathon, so we did not know what to expect. We learned a lot about building an application from scratch.

What we learned

We learned how to utilize more technologies, such as the variety of Python libraries we used, and gained more experience with AI and LLMS through Gemini. Beyond tech, we also better understood how our postures can affect us in the long run and key points to look out for. Alongside how we will approach the next hackathon with better time management and organization and not be afraid to branch out and go all-in on an ambitious project.

What's next

We plan on scaling this more through creating our own convolutional neural network and training it to our standards by having actual people be subjects and documenting their posture to provide our program with much better accuracy. Also, we would want to improve our user interface and include more features and customization for our users.

Analysis

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Technology

Found in codeClaimed only
  • PythonIn code
  • Google GeminiClaimed

1 of 2 appear in the indexed code. 1 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

18 KB

Source files

6

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.

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