IoT-Based Smart Home Energy Management System via Machine Learning Framework

Abstract

Through fast innovations in technology and the increasing availability of Internet of Things (IoT) devices, smart homes have emerged as a promising solution for enhancing energy efficiency and optimizing energy consumption. Smart homes utilize interconnected devices and sensors to automate and control various aspects of household operations, including energy management. Traditional home energy management systems typically rely on predefined schedules or manual user interventions to regulate energy usage. However, these approaches often lack adaptability and do not look at various aspects such as occupancy patterns, climate conditions, and individual preferences. This limitation delays the potential for achieving significant energy savings. To address these challenges, machine learning techniques have gained significant attention in the field of smart home energy management. Machine learning algorithms can analyse large volumes of data collected from IoT devices, identify patterns, and create precise forecasts about energy consumption. The approach enables concurrent checking, optimization and personalized control of energy usage within smart homes. Machine learning algorithms have been successfully applied to various domains, including energy forecasting and optimization. These algorithms can learn past energy consumption data and other important factors to learn complex relationships and generate actionable insights for energy management. Our study proposes an IoT-based energy management system for monitoring and controlling energy in homes. Energy monitoring technologies based on the IoT are now potentially extremely valuable for people living in big and traditional homes. This research presents a system that is an energy monitoring system and it is basically like a security camera for users through which they can examine how much power their homes have consumed and how much power consumption can be done in future. It can be simply synchronized with a web application for immediate access. In this project, our IoT device is a Smart energy device because we will fetch the data from the device through different sensors installed on it. It will provide the following statistics data from sensors such as temperature and humidity level, current and motion of a person in a room. The web application will have certain features like login, sign-in and test the power consumption using the unseen dataset. Moreover, for a better user experience, a graph as well as predicted values by model in the form of text will also be given through the web app.