Sustainable Smart Homes: Machine Learning for Energy Efficiency and Resource Optimization

Abstract

Smart homes equipped with AI-driven automation can play a crucial role in promoting sustainability. This paper explores machine learning techniques for optimizing energy usage, water conservation, and waste reduction in residential buildings. Predictive models, reinforcement learning, and edge AI are utilized to manage heating, ventilation, and air conditioning (HVAC) systems, optimize lighting, and reduce overall carbon footprints. The study also examines the role of AI-powered IoT devices in monitoring and controlling home energy consumption. Experimental results demonstrate how ML-based smart home solutions contribute to environmental sustainability and cost savings for consumers.