Published Paper Details:

The unprecedented rise in electrical energy consumption across residential, commercial, and industrial domains has made efficient monitoring, analytics, and control essential for cost savings and sustainability. Traditional metering systems typically provide only cumulative or coarse-grained readings, leaving users and managers without appliance-level insights or real-time alerts that could reduce wastage or prevent faults. This paper presents a comprehensive Internet of Things (IoT)- based power consumption and monitoring system that integrates voltage and current sensing, edge processing via a microcontroller, secure wireless transmission, cloud storage and analytics, and user-facing dashboards with control capabilities. The system measures instantaneous power and cumulatively computes energy usage per appliance using calibrated sensors (e.g., ZMPT101B and ACS712). An ESP32/Arduino reads the sensors, filters and timestamps data, and sends it to the cloud over MQTT/HTTPS. The cloud ingests data into a time-series datastore, runs analytics for peak detection and anomaly detection, and exposes dashboards and REST APIs for visualization and control. A relay driver stage enables remote actuation of connected loads for demand response or scheduling. Experimental deployment across multiple household appliances demonstrates measurement accuracy within acceptable error margins, consistent real-time reporting, and effective remote control. The design emphasizes modularity and scalability, allowing additional nodes to be added and future integration with machine learning for predictive maintenance and demand forecasting. This work shows that IoTenabled energy monitoring is a practical, cost-effective route toward smarter energy usage and tangible operational savings while providing a foundation for integration with smart grid and renewable energy systems.