Enelingo

Inspiration

We sat in the study room, drawing blanks on the whiteboard at 11:30pm for what direction our project would take, when all at once our Duolingo notifications for our lessons would go off. Without hesitation, we all took 5 minutes to complete our lessons and hopefully continue with our work, when the solutions struck us in the face. We had all managed to give priority to learning a language by making the engagement rewarding, why couldn't we do that with Energy? By getting people to care about consumption in a similar way, we could bring attention to energy usage to the general public under the guise of saving money, helping everyone involved.

What it does

Enelingo has its users create a profile with preliminary data, input energy-spending commodities, and set a budget limit themselves to. To make it easier for users to input their items, we use image recognition by integrating Google Cloud Vision. Then the app continually updates throughout the week on the energy expenditure of the user. Upon successfully staying under budget, the user has their streak score incremented and are informed much money they saved that week, encouraging continued use and reduced energy expenditures

How we built it

Enelingo has a database holding its users information in order to properly track their expenditures, and keep track of their progress. The database was built in MongoDB Atlas. We implement this database into a python file which serves as the backend of the app. The backend is in charge of updating user progression throughout the week and rewarding the user upon staying under budget. The UI was built in python using Kivy for ease of use. These parts where then integrated into the final project.

Challenges we ran into

We found it a challenge to implement Google Cloud Vision into our software. As well, finding a platform to work on took us a fair amount of time. Kivy also presented a lot of problems as we tried to learn to use it. Finally, the integration between frontend and backend poised a fair challenge.

Accomplishments that we're proud of

We believe that the UI we created is particularly intuitive and pleasing.

What we learned

Throughout this project we greatly improved our skills in using the Kivy package and Git. As well, we practiced integration between frontend and backend as well as with Google Cloud Vision

What's next for Enelingo

We would like to implement a notification system similar to Duolingo with its own iconic sound. We believe that having this would greatly improve user engagement and keep people accountable on their energy conservation journey. The addition of a total money saved metric may further encourage users to commit to their conservation goals. We also intend to make Enelingo a more communal platform, where people encourage one another to make eco-friendly choices the creation of a friend system, challenges and potential integration into other social media apps. General refinement of current features such as image recognition would improve functionality.