Easify

Emotion check notification
The various trackers
Home page
Attention graph
Site blocker
Music feature

Inspiration

As developers, we tend to face issues related to attention deficiency, poor mental health and a decrease in productivity due to staring at the screen all day.

What it does

Posture detection of the user and prompting if the posture is incorrect
Suggesting music to the user on basis of their emotions
Displaying graphs displaying attentiveness of the user
Suggesting Trending articles/repositories to users to cherish their knowledge
On basis of screentime, reminding the user to take refreshment breaks

Calming UI

Easify has a calming UI that is pleasing to the eyes and soothes the mind. This design is developed to enhance the productivity of the developers.

Pose Detection

Developers sit all day in front of their computers, and it's essential to keep in mind their health. Sitting in the wrong position is known to show a lot of adverse effects on the health of people. To resolve this issue, Easify has a pose detection model that tells the users if they are sitting in the wrong pose. It even highlights the percentage of wrong and correct poses using which users can correct pose.

Emotion Detection

Everyone talks about the physical health of the developers but what about their mental health? Studies have shown that mental health is the most important factor to keep a person productive in their work. So, Easify comes packed with an emotion detection model that predicts users' emotions from their facial gestures and sends frequent emotions to help the developers in tracking their emotions. These notifications also allow the users to play music if they are found to be sad or happy.

Mood-based music

Easify can detect users' moods/emotions from their camera but this is not it! We have enabled Easify to play uplifting music if they are sad and joyful music if they are happy. It is all done with the combination of Youtube API and Cockroach DB.

Attention tracker

Developers tend to lose focus while working. To make them more productive, Easify shows developers how attentive they were in the last 5 seconds. This attention tracker not only keeps a track of the head movement but also the movement of eyeballs which makes it super efficient in tracking the focus of the user.

Attention tracker graph

Users can also see the history of their attention and the number of times they were distracted by the means of a beautiful and easy-to-understand graph.

Refreshment break reminder

It is well known that taking breaks while doing your work increases productivity. So, to make developers more productive, Easify notifies them to take breaks after a fixed interval.

Website blocker

It is possible that users might try to use websites like Instagram and Facebook while focusing on their work thus reducing their productivity. So, to tackle this, Easify is equipped to block such websites with an inbuilt website blocking feature.

24/7 up-time

Easify is built to track users' productivity, and thus, Easify never rests, not even when Chrome is closed! Easify is always on its toes to serve its purpose of being a good productivity tool.

Security of users' data

All the classification and machine learning models are run in the users' browsers, and no data is transferred anywhere!

How we built it

In short, sweat and tears :') We split the code into parts based on the features. We've also created folders for the client and the server. We integrated CockroachDB with our backend and deployed it on Heroku. On the client-side, we integrated YouTube API and used 3 ML models for various features that we implemented.

Challenges we ran into

It was difficult to integrate Spotify API. Finally, we had to drop that idea because Spotify doesn't allow playback for non-Premium users.
It was difficult to integrate YouTube API too. Finally, we weren't able to play YouTube playlists on the extension so we resorted to playing individual songs.
It was difficult to figure out camera permissions in a Chrome extension
We were facing issues with CORS and content-script

Accomplishments that we're proud of

This thing actually works :)
We were able to use the camera for three different ML models (Pose detection, emotion detection, attention tracker)
We finally managed to play some music within the Chrome extension.

What we learned

How to create Chrome extensions
Integrating APIs in JavaScript
Handling large amounts of code and splitting them into different files
Learnt about CockroachDB and how to connect it with NodeJS backend
Deploying backend code on Heroku
How to work with YouTube APIs
How to work with Spotify APIs
Learnt about Face landmark detection and predicting the emotion of the user based on that
How to change scripts of other websites in order to block distracting websites