eunoia

Simplify tomorrow, tonight. Mornings are unpredictable and can be hectic. eunoia solves that issue by scheduling your tasks ahead of time, giving you peace of mind.

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Github: https://github.com/trwng/eunoia

Inspiration

To start our ideation, we looked into issues that we currently deal with. As students, we are constantly bombarded with work, and once we finish late at night, we wake up tired the next day to sluggishly make our way to school. Any unexpected events will result in students either missing out on rides or leading to complications with traffic/weather conditions. Therefore, we wanted to create a solution to this issue.

What it does

Eunoia allows the user to plan tomorrow's morning, lessening the stress and chaos that many people experience when they first wake up. Instead of having to open up 4 of your different devices, such as the Weather App, the Calendar App, checking Google Maps for traffic, and more, you're able to access all of those features in one app: Eunoia! Through Eunoia, you're able to see the current weather conditions, any tasks or events you listed for tomorrow morning, an ideal rest time, and a personalized AI chatbot who knows your habits and how to help you. Furthermore, we converted a model to help analyze your mood through your texts and help schedule your events and tasks. Eunoia was created to help those who are often stressed with the chaos every morning, and allows you to simplify it through one app.

How we built it

To create eunoia, we first documented all the issues that we face + the issues others often face on the web in a Google Document. Then, we had an envision of our design on Magma, and then used Canva to start our design. With the skeleton of our app, we then started on XCode and used SwiftUI, while one of the members started working on the model tracing and tokenizing on XCode.

Challenges we ran into

During this Hackathon, we faced challenges when we tried to use emotion to help organize the tasks in a manner that is suitable for the user's current emotions. We were unfortunately unable to implement this as we had problems tokenizing and tracing the pre-trained model.

Accomplishments that we're proud of

Our team is specifically proud of our progress on tracing the model and tokenizing. While we were unable to successfully tokenize the sentence and model tracing, we believe this hackathon served as a valuable experience and insight into what we should spend time learning.

What we learned

During this project, we were exploring ways to implement already trained models as our NLP. To accomplish this, we learned ways to trace train models using Python on Visual Studio Code, to then later have the model operate in our app.

What's next for eunoia

  1. Add a structured Firebase Cloud Storage system in order to create a user-by-user storage. We plan to do this by integrating
  2. Add more artificial intelligence to create specific diet plans for the user.

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