Abstract

In an era characterized by increased awareness of environmental concerns and the importance of energy conservation, the accurate prediction of individual energy consumption is a critical endeavour. This journal paper presents a comprehensive approach to forecast the energy usage of individuals by harnessing the power of machine learning algorithms. The study covers data collection, pre-processing, model selection, training, evaluation, deployment, and the interpretation of results. The primary aim is to empower individuals and utility companies with invaluable insights into predicting and optimizing energy usage, thereby reducing environmental impact and promoting energy efficiency.