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Design and Implementation of a Smart Home Energy Management System Using IoT and Machine Learning

Authors :
Devi M.
S. Muralidharan
R. Elakiya
M. Monica
Source :
E3S Web of Conferences, Vol 387, p 04005 (2023)
Publication Year :
2023
Publisher :
EDP Sciences, 2023.

Abstract

The paper “Design and Implementation of a Smart Home Energy Management System Using IoT and Machine Learning” proposes a system that aims to optimize energy consumption in a smart home environment. The system uses Internet of Things (IoT) devices to collect real-time data on energy usage and machine learning algorithms to predict future consumption patterns. This paper proposes the use of deep neural networks (DNNs) for the design and implementation of a smart home energy management system using IoT and machine learning techniques. The authors demonstrate the effectiveness of the system through experimental results, showing significant energy savings compared to traditional methods. The DNN is built using Keras or Tensor Flow and is trained on extracted features from energy consumption data collected using IoT sensors. The system is implemented with a real-time monitoring system and a user interface for remote access. The proposed system has the potential to save energy and reduce energy costs for households while providing real-time feedback to the user.

Details

Language :
English, French
ISSN :
22671242
Volume :
387
Database :
Directory of Open Access Journals
Journal :
E3S Web of Conferences
Publication Type :
Academic Journal
Accession number :
edsdoj.457be641e17e4c36b43eb5e09854f77d
Document Type :
article
Full Text :
https://doi.org/10.1051/e3sconf/202338704005