| Autor: |
Kumar Neeraj, Sundaram Kalyana, R. Reena, S. Madhumathi |
| Jazyk: |
English<br />French |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
E3S Web of Conferences, Vol 387, p 02002 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2267-1242 |
| DOI: |
10.1051/e3sconf/202338702002 |
| Popis: |
The increasing demand for energy utilization in smart homes has led to the exploration of machine learning techniques as a means to optimize energy consumption. This review paper explores the merits and demerits of using machine learning techniques for energy optimization in smart homes. Smart homes are becoming increasingly popular due to the potential benefits they offer, including increased energy efficiency, improved comfort, and enhanced security. However, to achieve these benefits, it is essential to optimize the energy utilization in smart homes. This paper presents machine learning techniques that have been used to optimize energy utilization in smart homes. In this paper proposed the using Stochastic Gradient Descent (SGD) algorithm for optimizing energy utilization in smart homes. However, challenges such as data privacy, accuracy of data collection, and cost may hinder the full adoption of these techniques. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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