Abstract:
The world is gearing towards renewable energy sources, due to the numerous negative repercussions of fossil fuels. There is a need to
increase the efficiency of power generation, transmission, distribution, and use. The proposed work intends to decrease household electricity use
and provide an intelligent home automation solution with ensembled machine learning algorithms. It also delivers organized information about the
usage of each item while automating the use of electrical appliances in a home. Experimental results show that with XGBoost and Random Forest
classifiers, electricity usage can be fully automated at an accuracy of 79%, thereby improving energy utilization efficiency and improving quality of life
of the user.
