AI-POWERED VOICE-CONTROLLED ENERGY TRACKING & BILL PREDICTION USING JAVA FULL STACK & ML

Abstract

In recent years, the demand for intelligent and efficient energy management systems has increased significantly. Traditional electricity meters only provide total energy consumption data and fail to offer appliance-wise monitoring, resulting in a lack of transparency and control over energy usage. This paper presents PowerVision, an AI-powered Smart Energy Tracker and Bill Predictor designed to monitor real-time, appliance-wise power consumption and predict future electricity bills using Artificial Intelligence (AI) and Machine Learning (ML) techniques. The proposed system bridges the gap between Electrical Engineering and InformationTechnology by integrating hardware sensors with a Java Full Stack web application. Real-time data from household appliances such as PC, fan, and bulb are collected using sensors interfaced with a microcontroller (ESP32) and stored in a MySQL database. The web-based dashboard, built using HTML, CSS, and Bootstrap, provides a responsive and user-friendly interface with graphical visualization of power usage and AI-generated bill prediction. Additionally, the system supports voice control features for enhanced interactivity. The implementation demonstrates accurate power tracking, intelligent bill forecasting, and an intuitive visualization platform that can be extended for residential and industrial applications. The project thus contributes to efficient energy

The system’s web interface, developed using HTML, CSS, and Bootstrap, displays detailed energy utilization, cost optimization, and smart energy management for the future.