Energy
Energy prediction
Predicting the energy consumption of energy appliances
energy electricity appliance prediction smart home

We used a wireless sensor network, which measured:


  • the temperature in different rooms of the house
  • humidity in different rooms of the house
  • temperature outside
  • humidity outside
  • wind outside 


We know the electric consumption.


We transformed the data to fit a classification problem.

We grouped the samples by intervals of energy consumption. Each one being a class in the final dataset.

So for example, between 0 and 200Wh belongs to class 0, between 200 and 400 to class 1 etc.

We have a total of 5 classes.


After training, we are able to predict future energy use.

Results from deployment:
90%
0.3kB
Accuracy
RAM used