EnergyTrack: A Data-Driven Approach to Monitor and Optimize Household Energy Usage

In the age of rising global energy demand, energy conservation is a crucial part of sustainable development. The design and deployment of an online Energy Consumption Tracker (ECT) that facilitates real-time tracking and analysis of energy consumption data is covered in the paper. Through the use of interactive dashboards, consumption prediction, and user-specific insights, the system helps users optimize their electricity usage. ECT offers effective and user-friendly energy management for homes and workplaces through IoT integration, data analytics, and visualization reporting tools. Lower energy costs and a smaller environmental impact are the outcomes of the proposed system's increased awareness of energy behavior. The paper also explores the use of machine learning for anomaly detection and predictive analytics. AI-driven consumption recommendations are among the upcoming improvements.