AI-Powered Energy Monitoring System
A smart IoT-based solution using ESP32 & PZEM-004T with AI-based prediction and Blynk visualization.
Project Information
- Category: IoT + AI
- Technology/Tools Used: ESP32, PZEM004T, Blynk
- Project Date: March 2025
- Status: Completed
Project Summary
This project focuses on building a complete end-to-end smart energy management solution that blends IoT sensing, real-time analytics, cloud visualization, and AI-based prediction. It showcases skills across embedded development, data processing, ML forecasting, and UI dashboard design—making it suitable for both core engineering and software roles.
About the System
AI-Powered Energy Monitoring System is an IoT-based smart energy analytics solution designed to monitor, analyze, and predict household or industrial power consumption in real time. The system uses an ESP32 WiFi-enabled microcontroller along with the PZEM-004T energy meter to measure voltage, current, power factor, active power, and total energy consumption.
The collected data is transmitted securely to the cloud and displayed through the Blynk IoT dashboard using real-time graphs, gauges, and indicators. This helps users visualize power usage patterns effortlessly.
A built-in machine learning model analyzes historical energy data to forecast future consumption trends, detect anomalies, and suggest optimization strategies—helping users reduce electricity bills and prevent overloads.
This system showcases strong skills in IoT hardware integration, embedded programming, cloud communication, machine learning, dashboard design, and real-time data visualization.