Knights' Wildlife Tracker

Inspiration

As wildlife lovers, we wanted to build a fun platform where people can easily share their wildlife sightings and connect with fellow nature enthusiasts. Our goal is to make it simple for everyone to enjoy and appreciate the outdoors while sharing those exciting moments with a community that cares about wildlife.

What it does

Knights Wildlife Tracker allows users to log wildlife sightings in real-time, upload images, and contribute to an interactive map. The app makes it easy for users to share their experiences and discover wildlife activity in the UCF area.

How we built it

We developed Knights' Wildlife Tracker using:

React for a responsive and user-friendly interface.
Node.js/Express for a robust backend capable of handling user data and requests.
Google Maps API for geolocation features that visualize sightings.
MongoDB for seamless image uploads and management.

Challenges we ran into

During development, we faced multiple challenges, including:

Ensuring that each uploaded image accurately pins to the corresponding location on the map required a moderate amount of research and testing.
We initially aimed to incorporate visual recognition technology to help identify animals in user-uploaded photos. This proved to be a greater challenge than we anticipated, so we chose to redirect our efforts toward other features that would provide more immediate value to our users.

Accomplishments that we're proud of

We successfully created a functioning prototype that features a sleek user interface and effectively integrates the Google Maps API for real-time geolocation of wildlife sightings. We're proud of how these elements come together to deliver a smooth and intuitive experience for users interested in tracking wildlife.

What we learned

We learned how crucial it is to stay flexible during the development process and to adapt our plans based on what works best for the project. We also gained valuable experience in integrating databases and tackling the technical challenges associated with geolocation features.

What's next for Knights' Wildlife Tracker

Looking ahead, we plan to enhance the application by integrating machine learning algorithms for species identification based on user-uploaded images. We also aim to add community engagement features to foster interaction among users.