AI-Powered Energy Consumption Optimization for Smart Homes Using IoT

Abstract

Energy management in smart homes is one of the many facets of daily living that have been changed by the integration of Artificial Intelligence (AI) and the Internet of Things (IoT). This study investigates the design and execution of an artificial intelligence (AI) driven system for IoT-enabled smart home energy optimization. This study’s main goal is to provide a framework that uses AI algorithms and Internet of Things sensors to efficiently control and optimize energy use. The system attempts to ensure user comfort and convenience while optimizing energy efficiency through real-time data collecting and analysis. The suggested system’s architecture is covered in the paper. It comprises Internet of Things (IoT) devices placed throughout the smart home to track the energy usage patterns of various appliances and gadgets. Artificial intelligence (AI) technologies, such as machine learning and deep learning models, then evaluate and analyze this data in order to forecast energy demands and optimize usage appropriately. The study also discusses the difficulties in putting such a system into practice, such as interoperability, security, and data privacy concerns. In order to guarantee the smooth integration and functioning of the AI-powered energy optimization system, strategies and solutions for addressing these issues are also put forth. The efficacy and performance of the suggested system are assessed using simulations and real-world trials, showing notable gains in cost and energy efficiency over conventional methods.