Hydro powerplants in Scandinavia fail to harness a potential profit of 6 million EUR annually,
because current modeling techniques are not enough for the rate of ice melting.
We deliver Machine Learning techniques for these operators to respond in time,
capture potential profit that while increasing energy efficiency.
🚀 EU space technologies
Copernicus Sentinel 2 satellite data. Datasets on ice cover, and water flow monitoring
Copernicus Marine Environment Monitoring Service data
❄️ Connecting the Arctic
We approached the theme #2 Life on Land for climate change adaptation.
The Artic region increases production capacity from hydro power, one source of renewable energy.
🤖 Technical aspect
Using machine learning to predict top k-best locations for water potential.
Data: time-series data of coordinates of present power plants are indicated as good locations, along with the other land-related oriented.
- Features: satellite images, coordinates of good locations, snow coverage, ice peak, water velocity, elevation
- Label: k-best locations -> most optimal one
Our team consists of a Product-owner, a Designer, a Bussines hustler, a Tech deep-mind,
- Nguyen Thanh Tuan - Machine Learning enthusiast (a humble guy refusing the title "ML engineer")
- Thai Thi My An - Graphic Designer (drawing alluring arts)