Inspiration
We were so desperate to solve the question and after googling for numerous vague solutions, we were frustrated by the fact of not finding anything good. We Decided to narrow down our problem statement to target single thing and solve it to help both DISCOM and customer.
What it does
Soon when we were out of ideas we decided to try to find what appliances are running in a current time frame based on the fact we have a combined load of all the devices and use the predicted appliances ideal vs current usage pattern to find inefficient appliances.
How we built it
We Started with Building UI/UX first. Then The ML team was mainly focused on finding insights whereas backend/frontend started to implement APP in (sails/node/mongo and react native).
Challenges we ran into
The frustration of not being able to come with something new for half the time.
Accomplishments that we're proud of
We Did found a unique solution
What we learned
Problem Solving
What's next for naag shakti
WIN
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