Inspiration
The inspiration for this project was to help see the energy increase in today's world to help make people aware of the impending energy crisis. With more attention drawn to this problem, the more people will be motivated to make solutions to tackle the issue.
What it does
Our model accurately predicts the energy consumption of different counties in the US over the following years, based on various factors like location, future population and previous year trends
How we built it
There were two aspects to our project, backend and front end. On the backend, we made a machine learning project that uses linear regression to predict the future energy usages. In the front end, we used Django and Flask.
Challenges we ran into
We ran into various challenges, including not being able to transform and format data collected from the website properly, using Flask and Django as first time users, etc.
Accomplishments that we're proud of
We are proud of the accuracy of our model. It received an R-Squared value of 98% and the results seemed quite reasonably well. We were also able to troubleshoot everything related to it in the time of the hackathon. We were also able to successfully make a website using Django and Flask python frameworks, something we have never worked with before.
What we learned
We learnt to manage our time and set expectations, as in the world of tech there are always unknown variables and things often don't go according to plan
What's next for EnergyAI
We would like to expand our region across the world and make it specific to people's personal habits, so that we can identify exactly what factors affect large consumption of energy
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