MOP: Mood Optimizing Project

Our team has developed a website that users can utilize to improve their mental health. Whether you are sad, angry, or stressed, our application has a suggestion you can use to improve your mood.

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Inspiration

We came up with this project by looking at the current COVID-19 pandemic situation. Due to the pandemic, many people are facing mental health challenges due to various reasons, such as isolation, online classes, and the impact on social activities. As well, we all know what it’s like to be stressed due to workload, new situations, and other issues. Therefore, we decided to develop a project that would address these problems.

What it does

Our application has several mood selections you can choose from depending on how you feel on a certain day. Depending on whether you choose sad, angry, or stressed, the user interface will lead to several activity suggestions based on your mood.

How I built it

Technologies we used for front and back end were React, for the app UI, Github, for sharing and compiling code, Visual Studio Code, for code editing and local work, Firebase, for the database, and JavaScript, as the main coding language we used throughout.

Challenges I ran into

This is the first hackathon for all our team members, so there was a lot of confusion on what to do and how to execute our project. However, our team was able to communicate well with each other despite not knowing each other prior to this hackathon, which made it easier to decide on a project that was doable with everyone’s skills. As well, individual researching and learning about coding concepts on our own helped.

Accomplishments that I'm proud of

Completing the basics of how we wanted it to look like.

What I learned

Javascript code and how to build UI with React

What's next for MOP: Mood Optimization Project

For the future of the project, we would like to add features we planned to add but couldn’t during this hackathon, such as:

  • Finding a fix to order the list of activities based on the frequency of clicks which we failed to solve due to constrained time.
  • Include likes/dislikes ratio, favorites, frequency as additional sorting parameters
  • Analyze the sentiment of Users input (a paragraph or a sentence) to detect emotion
  • Better UI, Code Organization, Descriptive variable naming and increased code Modularity.
  • Database Management, User Registration and Login.
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