Smart Metering for Real-Time Power Prediction Price Forecasting and Intelligent Alerts in Modern Living Spaces

This study introduces a novel approach to providing intelligent energy-saving solutions for traditional households through a smart meter powered by artificial intelligence. The suggested smart meter uses historical data collection and machine learning algorithms to anticipate power usage and electricity pricing for the next month. Unlike existing approaches that require several sensors for optimal energy efficiency, the suggested smart meter uses real-time IoT data collection and machine learning algorithms. The proposed system uses a long short-term memory (LSTM) based machine learning forecasting model, which accurately predicts energy consumption compared to traditional techniques. Furthermore, a threshold-based warning mechanism alerts users of excessive power usage, allowing for cost-effective energy management. The suggested method increases user awareness, lowers energy consumption, and promotes sustainable living by optimizing power use with its easy integration into home settings and ability to monitor the real-time power delivery to loads.