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A screenshot of our product in action
Slideshow
Our google slideshow to our pitch is attached here: https://docs.google.com/presentation/d/1UYMao3JREeiSHhkGyOB-N0s1mNK9u0ZAbihDd2CwUAs/edit?usp=sharing
Inspiration
Climate change is steadily raising temperatures, threatening our planet's habitability. Our dependence on fossil fuels releases greenhouse gases, warming the Earth and exacerbating climate change. Renewable energy is a solution, but its effectiveness is hampered by inefficient placement, such as with wind turbines.
What it does
The user can pick a location on an interactive map and see the wind turbine's power percent efficiency in real time. Additionally, the user can see the past weather trends of the area to determine whether the location they picked is an optimal spot to place a wind turbine. The wind turbine efficiency was determined using a Machine Learning algorithm built from Wind Turbine real-world datasets.
How we built it
Python, Sci-kit Learn, flask, HTML, CSS, JS (Blood, sweat, and tears)
Challenges we ran into
- Training the model
- Async with Javascript
What's next for WindMax: An AI Wind Turbine Placement Optimizer
We aim to consider other factors for wind turbine placement, such as
- Proximity to power suppliers
- Check if the location is on open land rather than forests
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