AI+IoT Based Energy Monitoring & Predictive Power Analytics System: A Review

Abstract

The increasing demand for electricity has created a need for intelligent and efficient energy monitoring and management systems. Traditional energy monitoring systems mainly provide basic consumption measurements and have limited capabilities for prediction and abnormal usage detection. This review paper presents an overview of AIoT-based intelligent energy monitoring and predictive power analytics systems, focusing on the integration of Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), cloud platforms, and real-time dashboards. The review examines existing techniques for real-time measurement of voltage, current, power, and energy consumption, along with AI/ML methods used for energy consumption forecasting and anomaly detection. It also compares existing approaches based on monitoring capability, prediction accuracy, anomaly detection, cloud integration, and intelligent analytics. The study identifies major challenges and research gaps in developing a unified system that can provide real-time monitoring, accurate power-demand prediction, abnormal usage detection, alerts, and energy cost estimation. Finally, the paper discusses future opportunities for smart homes, industries, offices, and commercial buildings, with the aim of improving energy efficiency, reducing energy wastage and supporting sustainable energy management.