Volume no :
9 |
Issue no :
1
Article Type :
Scholarly Article
Author :
Mr. Selvaprasanth P
Published Date :
May, 2025
Publisher :
Journal of Artificial Intelligence and Cyber Security (JAICS)
Page No: 1 - 11
Abstract : The increasing demand for sustainable energy consumption and the proliferation of smart devices have driven the development of Intelligent Home Energy Management Systems (HEMS). This paper proposes a novel IoT and AI-driven HEMS that enables real-time monitoring, control, and optimization of household energy usage. By integrating smart sensors and appliances with a centralized IoT gateway, the system collects real-time energy data, which is then processed using advanced predictive analytics based on machine learning algorithms. The system learns user behavior, weather patterns, and energy pricing models to forecast consumption and suggest optimal usage schedules. Additionally, it can automate load shifting and appliance control to reduce peak demand and energy costs while enhancing user comfort. The proposed HEMS aims to contribute to smarter grid interactions, increased energy efficiency, and a reduction in carbon footprint. Simulation and experimental results demonstrate the system’s effectiveness in achieving significant energy savings and intelligent decision-making.
Keyword Home Energy Management System (HEMS), Internet of Things (IoT), Artificial Intelligence (AI), Predictive Analytics, Smart Grid, Energy Optimization, Load Forecasting, Machine Learning, Energy Efficiency, Demand Response.
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