Paper Title: An overview of Optimization and learning algorithms for energy management in smart homes
Authors: Andile Ngcobo, Bongumsa Mendu, Bessie Baakanyang Monchusi
Corresponding Author: Bongumsa Mendu (mendubongumsa@gmail.com), South Africa
Abstract
Smart home electric energy management systems are designed to optimize energy efficiency, reduce waste, and promote sustainability. This paper aims to conduct a literature review on optimization and learning algorithms for energy management in smart homes. The research methodology involves retrieving data from the Scopus database and visualizing the information through VOSviewer. The results of the literature reviewed encompass a wide range of strategies and algorithms aimed at optimizing energy management in smart homes. A key noticeable aspect is the diverse application of advanced optimization techniques and machine learning algorithms to enhance energy efficiency, reduce costs, and promote sustainability. The study contributes by providing an in-depth analysis of optimization algorithms for energy cost reduction, evaluating and categorizing learning algorithms, and identifying best practices for optimizing energy consumption in smart homes.
Keywords
Optimization, Learning algorithms, Energy management, Smart homes
Cite:
Ngcobo, A. ., Mendu, B. ., & Monchusi, B. B. . (2025). An overview of Optimization and learning algorithms for energy management in smart homes. Future Sustainability, 3(1), 14–20. Retrieved from https://fupubco.com/fusus/article/view/233
