We were inspired to create a project that would have a large scale impact and was an application of interested of ours.
What it does
The project uses a machine learning algorithm based on employee schedule data to predict and autonomously change the temperature in rooms according to usage and patterns.
How we built it
We used GCP computer engine vm to use Keras, we also used GCP app engine for hosting our Flask server, we used GCP cloud storage for storing population time series data of how many people are in rooms and for how long. Additionally, we built a dashboard in Reactjs to display information to a company of how their rooms are being used.
Challenges we ran into
A large part of the challenges we faced were in terms of integrating all the services together.
Accomplishments that we're proud of
Creating a high accuracy model, working well as a team and creating a cool app.
What we learned
We learned how to GCP for different purposes.
What's next for Pi-Sensor
The sky's the limit.
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