Big Data-Intelligence Analytics for Energy Optimization in IoT-Enabled Smart Home Devices

IF 10.9 2区计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Transactions on Consumer Electronics Pub Date : 2025-04-29 DOI:10.1109/TCE.2025.3565590

Yihong Li;Qiang Song

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引用次数: 0

Abstract

This article explores the integration of Artificial Intelligence (AI) and Big Data Analytics to optimize energy consumption in IoT-enabled smart home devices. It presents a robust analytical framework that leverages Variational Autoencoders (VAEs) for feature extraction and Differential Evolution (DE) for optimizing energy management parameters. Data was gathered from various IoT devices, including energy usage patterns, occupancy data, and environmental conditions. The results show a notable 40% reduction in energy consumption, leading to annual cost savings of up to

${\$}300$

per household. Moreover, user satisfaction increased by 25%, with participants reporting heightened awareness and engagement in energy conservation. The study highlights how the proposed framework efficiently identifies common usage patterns and optimizes energy distribution while preserving user comfort. These findings reinforce the potential of AI-driven analytics in improving energy efficiency in smart homes, demonstrating that advanced algorithms not only support energy conservation but also promote active user participation in sustainability efforts.

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面向物联网智能家居设备能源优化的大数据智能分析

本文探讨了人工智能（AI）和大数据分析的集成，以优化支持物联网的智能家居设备的能耗。它提出了一个强大的分析框架，利用变分自编码器（VAEs）进行特征提取，差分进化（DE）优化能源管理参数。从各种物联网设备收集数据，包括能源使用模式、占用数据和环境条件。结果显示，能源消耗显著减少了40%，每户每年可节省高达300美元的成本。此外，用户满意度提高了25%，参与者报告说节能意识和参与度提高了。该研究强调了所提出的框架如何有效地识别常见的使用模式，并在保持用户舒适度的同时优化能源分配。这些发现加强了人工智能驱动的分析在提高智能家居能源效率方面的潜力，表明先进的算法不仅支持节能，还促进了用户积极参与可持续发展工作。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Consumer Electronics 工程技术-电信学

CiteScore

7.70

自引率

9.30%

发文量

审稿时长

3.3 months

期刊介绍： The main focus for the IEEE Transactions on Consumer Electronics is the engineering and research aspects of the theory, design, construction, manufacture or end use of mass market electronics, systems, software and services for consumers.