Inspiration
Street lights around us have multiple problems which were provided to us as problem statements and we brainstormed on those statements and came up with brilliant solutions.
What it does
Our device, which costs less than 10 rupees per piece, is a robust and integrated solution which adds on to the existing infrastructure without interfering with it. Hence it is a solution which can be used without hassle
How we built it
We built nodes using tree topology to sent bits. These were recorded to identify error locations. This was further visualized on a dashboard and machine learning was used to predict faults. Complaint handling was also improved.
Challenges we ran into
Reducing the cost of a single node to minimize the initial setup cost. Effectively maximize maintenance and revenue generation.
Accomplishments that we're proud of
A massive reduction in the cost of the setup and using advanced modules and technology stack to effectively utilize users' complain to accurately predict and prevent light functioning.
Built With
- analytics
- android-studio
- api
- firebase
- firestore
- github
- google-maps
- heroku
- iot
- machine-learning
- mapquest
- node.js
- nodemcu
- python
- rf-boston-predictive-darksky-aadhar
- vue


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