HeadCount

Settings Screen
Login Screen

Inspiration

The idea for HeadCount came from a career fair, where we noticed employees standing outside the event with clickers to track the number of people entering and exiting, ensuring they didn't exceed the maximum occupancy. This manual process seemed inefficient and prone to errors. We realized that with an automated system, this task could be streamlined, eliminating the need for multiple people to manage occupancy manually. By implementing our solution, we save time, effort, and money. For example, assuming there are 5 rooms with 2 people manning each room at $14.35 per hour, our HeadCount program saves $574 per career fair.

What it does

HeadCount is an automated system that counts the number of people in a room and relays that information to a central dashboard. It tracks occupancy levels in real-time, notifying you when the room is near or has reached its maximum occupancy. This ensures compliance with safety regulations while reducing the need for manual counting at entrances.

How we built it

We used a combination of technologies to build HeadCount:

Frontend: Next.js and React
Backend: FastAPI
Machine Learning: YOLO library for people detection
Version Control: We employed a Git branch workflow to organize and track changes Each team member was assigned roles based on frontend, backend, and UI/UX, but we collaborated on various tasks to get the project completed.

Challenges we ran into

As most of us were new to programming, we encountered several challenges:

Setting up our development environments and learning Git
Navigating the new tech stack we were working with
Resolving multiple Git conflicts during collaboration
One team member had an allergic reaction, which forced us to cut the day short

Accomplishments that we're proud of

Despite the challenges, we successfully built a functional prototype of HeadCount. This was an incredible achievement for the team, especially considering three of our members were participating in a hackathon for the first time. We learned new technologies, collaborated effectively, and overcame unexpected setbacks.

What we learned

Throughout this project, we learned:

Git flow and effective version control strategies
New technologies including Python, Next.js, React, FastAPI, and YOLO for machine learning
Basic software engineering practices and how frontend and backend systems integrate into a complete solution