An intelligent IoT-based home automation for optimization of electricity use

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Date

Authors

Francis, Antony
Madhusudhanan, Sheema
Jose, Arun Cyril
Malekian, Reza

Journal Title

Journal ISSN

Volume Title

Publisher

Wydawnictwo SIGMA

Abstract

The world is gearing towards renewable energy sources, due to the numerous negative repercussions of fossil fuels. There is a need to increase the efficiency of power generation, transmission, distribution, and use. The proposed work intends to decrease household electricity use and provide an intelligent home automation solution with ensembled machine learning algorithms. It also delivers organized information about the usage of each item while automating the use of electrical appliances in a home. Experimental results show that with XGBoost and Random Forest classifiers, electricity usage can be fully automated at an accuracy of 79%, thereby improving energy utilization efficiency and improving quality of life of the user.

Description

Keywords

Smart home automation, Ensembled, Machine learning algorithms, Microcontroller, Proximity sensors, Sowa kluczowe, Automatyka domowa, Optymalizacja zuycia energii, Mikrokontroler, Czujniki zblieniowe, SDG-07: Affordable and clean energy, Internet of Things (IoT)

Sustainable Development Goals

SDG-07:Affordable and clean energy

Citation

Francis, A., Madhusudhanan, S., Jose, A.C. et al. 2023, 'An intelligent IoT-based home automation for optimization of electricity use', Przeglad Elektrotechniczny, vol. 99, no. 9, pp. 123-127. DOI: 10.15199/48.2023.09.23.