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.