We were inspired by other integrations of artificial intelligence in everyday life and decided that we could incorporate it into this project as well. The workshop held by CSA's Dr. Martin today really showcased to us the issues astronauts face in space and this motivated us to come up with a solution to help give them some ease of access and address their biggest issues while traveling.

What it does

Our application records user-profiles and utilizes the information provided in a variety of calculations to determine the user's mental & physical health, caloric intake, exercise, etc. It also has inventory calculations and an algorithm to check if the rations in the inventory are sufficient to last the rest of the trip. We made our program very open-ended meaning it could be utilized for any future space travel and to any planets, not just Howler. This makes this project a lot more large-scale and ambitious than if it only worked for the travel plan to planet Howler.

How we built it

Utilizing a locally hosted database via MongoDB to store user information, Node.js for all the back-end communication/algorithms, and CSS as well as Jade for the actual web development (front-end), we created our application. We custom-coded every line of our website and application, and everything you see is completely made by us including the logos.

Challenges we ran into

We ran into various challenges, primarily being over-ambitious which led to us realizing the harsh reality of a time constraint. We had a really ambitious idea, and wanted to make our project very aesthetic and focus on the UX aspects as well, however, decided to sacrifice some of the aesthetic in order to focus on the actual implementation of our concepts.

Accomplishments that we're proud of

Managing to finish this project in the limited time we had felt very accomplishing to us, and we're especially proud of our medical-diagnosis system as it addresses such a large issue astronauts have to face.

What we learned

We learned how to use MangoDB and Node.js to a higher degree than when we originally started this project, as working over all the bump helped us improve. We learned how to collaborate very well, and researched a lot about medical technologies and issues that can occur in space.

What's next for RASU-AI

We plan to implement a full-fledged AI with machine learning that will take information from the datasets and user profiles to improve its' medical diagnosis every time!

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