carvia

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  Solution diagram

Inspiration

Saving energy efficiency problems using technology (IoT, Apps and scalable backends)

What it does

Solving problems in Smart Electric Meters using data science, IoT and scalable backends.

How we built it

We have built a prototype that mocks the peak load on a given sub station and transmits this data back to smart meters so that IoT enabled devices installed in the household can react to feedback and adapt accordingly.

Challenges we ran into

1. Time constraint
2. Lack of IoT hardware available for real demonstration
3. 2 team members could not join the hackathon, so we were left with team of 2 only.

Accomplishments that we're proud of

1. we built a demonstrable prototype around ToU variable charging.

What we learned

What's next for carvia

1. Developing real prototype around city load aware devices using IoT technology, that can adapt themselves to low energy mode when city load is at peak.
2. Using machine learning algorithm to detect defaulters and categorize users into different segments.
3. Create Android App that serves the customers and provides capabilities like - bill payment, show realtime un-billed amount, show planned power outages in a given area.
4. Creating weather aware ML driven APIs that can automatically switch off agricultural pumps if there is a rainfall prediction in next X hours.
5. Recommending EESL products to users based on their power consumption and location. Basically a localized recommendation platform using ML algorithms.
6. Create a secure and scalable backend platform that follows microservices architecture to serve huge volume of requests.

Built With

• android
• iot
• java
• machine-learning
• mqtt
• python