Machine Learning for Energy Consumption Optimization in Smart Homes

Abstract

Smart homes equipped with intelligent systems can significantly optimize energy consumption by using advanced machine learning (ML) techniques. This article explores the role of machine learning in optimizing energy usage in smart homes, focusing on the application of algorithms that predict energy consumption patterns, optimize device usage, and integrate renewable energy sources. The paper discusses the various ML techniques used in smart homes, such as supervised learning, reinforcement learning, and neural networks. Furthermore, the article explores challenges related to data quality, real-time processing, and privacy issues, offering solutions and future directions for improving energy efficiency.