Enhancing Energy Efficiency With Smart Building Energy Management System Using Machine Learning and IOT

Abstract

The energy management system designed on the networking platform has been interfaced with controller to control the electrical device using the Wireless communication has been used as the most reliable and efficient technology in short-range communication. In this method IoT-based energy management could significantly contribute to energy conservation of home appliances device. This model analyses an IoT-based smart energy meter that automatically tracks residential energy consumption using current and voltage sensors. Input values senses unit that detects and controls the electrical devices used for daily actions. The ESP32 is used due to its built-in Wi-Fi facility, allowing data collection and exchange from electronic hardware to a cloud platform. The virtual android app displays the value of voltage, current, power, and unit consumed on a mobile screen, enhancing the efficiency of the system. The developed coding system to enhance system performance and provide more accurate results and ESP32 controller to interface non-invasive CT and voltage sensors, delivering data to a Blynk server over the internet. Model show the system accurately records voltage, current, dynamic power, and increasing power consumption and outcome accordingly, the home concerned person can turn ON/OFF the device based on such information if customer based user information.