Machine Learning Prediction Based Integrated Smart Energy Management System to Improve Home Energy Efficiency

This paper proposes an integrated smart energy management system that applies different machine learning regression techniques to gather, enhance, and prepare various relevant data taken from the surrounding environment to predict and schedule the running periods of one of the schedulable appliances in the household. The system was applied to a case study with encouraging results showing energy consumption reduction rates up to 36%.