ANTsy

Main Page
Recommendations (based off a personalization quiz)
User settings
Recommendations
Add a review to a hike
See general consensus from community
View a user's hike history
Add a hike event

Inspiration

As college students in stem, life can get busy and we need time in the outdoors to destress. Sometimes all you need to do is get some Vitamin D and a fresh breath of air. But more often that not, finding where to hike to get that experience is tough, especially when you're traveling to a new place. We have all had experiences scouring the internet and filtering through different websites trying to find the hike that fit all of our preferences. That's what ANTsy was made for; When you're feeling antsy to go on a hike, it'll find the perfect match for you.

What it does

Our website allows the user to find a tailored hike specific to their needs and wants. They start by having you decide the type of scenery, difficulty, distance you're willing to travel, and things you want to see on your hike. It then gives a custom list of trails based on your preferences, with details about length, elevation, and location. Users can post reviews and photos to the hikes, and each review you post is saved as a hike you've been on in your profile, making it easy for you to document your experiences and remember the hikes you'd love to do again.

How we built it

The backend runs on AWS Lambda (server-less), and we used the AWS SAM CLI tool to streamline development and deployment of code changes. Authentication is managed through Auth0, while general user information is stored in an AWS DynamoDB table. Hikes (and hike info) is also stored in a DynamoDB table, along with user hike reviews. AWS Bedrock is used to recommend hikes to users based on their preferences quiz. Users can upload images to their hike reviews, which are stored in Amazon S3. The frontend code is deployed using Amazon S3 and CloudFront, and is implemented using React.js (for general UI). Hiking data was pulled from an open trail dataset, and displayed using the Google Maps API.

Challenges we ran into

Most of our members have never touched AWS services before, and the couple that have had only used 1-2 services briefly. This made it hard for us to divide the work at first, as we needed to get familiar with the tools before we could declare any strong plans. Also, since we were using so many services, and combining so many domains (AWS, Google Suite, Auth0...), there was a lot of struggle in authenticating and managing access correctly, as well as merging with other people's builds.

Accomplishments that we're proud of

We managed to accomplish all that we were set out to do - an AI recommendation system, an authenticated login portal, the ability to favorite, share, and customize hikes, and of course, the significant and meaningful use of AWS services. Of course, our app is far from perfect, but it is cohesive, complete, and features an adorable little ant mascot.

What we learned

AWS is not as complicated as it seems, especially if you have the freedom to try as many services as you want without consequences (for the most part)
You can probably find an Amazon web service for any use-case you can think of
Don't use any random AI coding editor when you have access to the coding editor directly from Amazon (Kiro)

What's next for ANTsy

With more time, we would love to expand it to be an even larger social platform. Our ant mascot was inspired by how ants form trails by following their friends. In a similar fashion, antsy is aimed to be a social hiking platform that lets friends share their favorite hiking spots with each other. We would do this by: