QueTal

• 

  This is a view of all tasks for that day by hour.

• 

  This is where the user can input a task which is added to the list of all tasks.

Inspiration

As college students, we're so busy that we often lose track of our time. How productive are you really and what makes you truly satisfied in your day to day life?

What it does

Input your schedule in QueTal, and it will visually summarize tasks and events for you. Rate your every moment and you'll know how you're really doing. Maybe you'll start noticing the subtleties in your life, like on whether you're sleeping enough, spending time with friends, or not getting work done.

How we built it

We built the frontend using React Native. The ML model was written in JavaScript. We have a cockroachDB cluster, which we would like to connect to the mobile app.

Challenges we ran into

Even though we had individual components rendered and got clean looking UI's for them, we struggled to compile them all in a smooth way to seamlessly transition between them. Similarly, finding a good machine learning function to map our inputs to our outputs was also a difficult process.

Accomplishments that we're proud of

We learned how to build apps with react native and gained a solid understanding of how different components inherit properties from each other. Additionally, we got a working understanding of how to train a machine learning algorithms that uses linear regression, when a data set it provides.

What's next for QueTal

We can get automatic scheduling so that when an event or task is entered into the app, it can automatically find time to schedule them. Additionally, we can improve our ML learning model so that it can get a better formulation of input factors like productivity and happiness to determine a sense of self satisfaction per the day.

Built With

• cockroachdb
• javascript
• react-native