Intelligent Temperature Control System Utilizing Gated Recurrent Units and the Internet of Things
Existing temperature control systems are increasingly inadequate in addressing the dual demands of energy conservation and enhanced quality of life owing to their limited adaptability and predictive capabilities. Traditional intelligent temperature control systems, including earlier intelligent mode...
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Published in | Journal of Digital Contents Society Vol. 25; no. 11; pp. 3419 - 3429 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
한국디지털콘텐츠학회
30.11.2024
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Subjects | |
Online Access | Get full text |
ISSN | 1598-2009 2287-738X |
DOI | 10.9728/dcs.2024.25.11.3419 |
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Summary: | Existing temperature control systems are increasingly inadequate in addressing the dual demands of energy conservation and enhanced quality of life owing to their limited adaptability and predictive capabilities. Traditional intelligent temperature control systems, including earlier intelligent models, often lack dynamic adjustment and predictive mechanisms, leading to reduced user comfort and suboptimal energy efficiency. This paper proposes an intelligent temperature control system that integrates the Internet of Things (IoT) and gated recurrent units (GRUs) to enhance living comfort and optimize energy usage. The system collects real-time data through IoT sensors, utilizing the GRU to learn user behavior patterns and environmental fluctuations, dynamically adjusting energy-saving modes to maximize comfort while significantly reducing energy consumption. Experimental results demonstrate that the system improves temperature prediction accuracy, reduces energy consumption, and enhances user comfort. This research lays both theoretical and practical foundations for future intelligent home temperature control systems. Despite some limitations, with further optimization and scaling, this system has the potential to become a key technology in smart home applications, paving the way for broader adoption of smart home solutions. KCI Citation Count: 0 |
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ISSN: | 1598-2009 2287-738X |
DOI: | 10.9728/dcs.2024.25.11.3419 |