Integrating AI and IoT for Smart Home Energy Management

Abstract

This research introduces a smart IoT (Internet of Things) system for enhancing household energy efficiency by integrating real-time electricity monitoring, predictive analytics, and AI (Artificial Intelligence)-driven personalized guidance. Traditional home energy management often lacks a level of detail, leading to uninformed usage patterns and increased energy waste. The developed system consists of a developed IoT-enabled monitoring unit, time-series forecasting, and generative AI to deliver proactive and intelligent electricity management experience. The IoT-enabled unit monitors individual appliance consumption and implements threshold-based control mechanisms to prevent overuse. The machine learning algorithm analyzes historical usage data to forecast future electricity demand, supporting preemptive consumption planning. The Large Language Model (LLM) generates personalized energy-saving recommendations based on the overall electricity usage data collected from the system. Power monitoring portal enhances user interaction through real-time energy movements and feedback mechanisms. This study contributes to sustainable living by promoting energy-conscious behavior, reducing household energy expenditure, and aligning domestic energy usage through a data-driven solution.