A Scalable and User-Friendly Framework Integrating IoT and Digital Twins for Home Energy Management Systems

The rise in electricity costs for households over the past year has driven significant changes in energy usage patterns, with many residents adopting smarter energy-efficient practices, such as improved indoor insulation and advanced home energy management systems powered by IoT and Digital Twin technologies. These measures not only mitigate rising bills but also ensure optimized thermal comfort and sustainability in typical residential settings. This paper proposes an innovative framework to facilitate the adoption of energy-efficient practices in households by leveraging the integration of Internet of Things technologies with Digital Twins. It introduces a novel approach that exploits standardized parametric 3D models, enabling the efficient simulation and optimization of home energy systems. This design significantly reduces deployment complexity, enhances scalability, and empowers users with real-time insights into energy consumption, indoor conditions, and actionable strategies for sustainable energy management. The results showcase that the proposed method significantly outperforms traditional approaches, achieving a 94% reduction in deployment time and a 98% decrease in memory usage through the use of standardized parametric models and plug-and-play IoT integration.

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Publication Details

Journal
Applied Sciences
Published
2024-12-18
DOI
https://doi.org/10.3390/app142411834
Citations
15
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
3.13

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article

A Scalable and User-Friendly Framework Integrating IoT and Digital Twins for Home Energy Management Systems

Orfeas Eleftheriou, Vasilis Naserentin, Anders Logg, Stelios Krinidis et al.
15 citations
Applied Sciences
Smart Grid Energy Management
3.13
article

A Scalable and User-Friendly Framework Integrating IoT and Digital Twins for Home Energy Management Systems

Orfeas Eleftheriou, Vasilis Naserentin, Anders Logg, Stelios Krinidis, Asimina Dimara, Christos‐Nikolaos Anagnostopoulos, Alexios Papaioannou, Mariya Pantusheva, Christoforos Papaioannou, Ioannis Tzitzios, George Spaias, Myrto Stogia
article en
15 citations

Abstract

The rise in electricity costs for households over the past year has driven significant changes in energy usage patterns, with many residents adopting smarter energy-efficient practices, such as improved indoor insulation and advanced home energy management systems powered by IoT and Digital Twin technologies. These measures not only mitigate rising bills but also ensure optimized thermal comfort and sustainability in typical residential settings. This paper proposes an innovative framework to facilitate the adoption of energy-efficient practices in households by leveraging the integration of Internet of Things technologies with Digital Twins. It introduces a novel approach that exploits standardized parametric 3D models, enabling the efficient simulation and optimization of home energy systems. This design significantly reduces deployment complexity, enhances scalability, and empowers users with real-time insights into energy consumption, indoor conditions, and actionable strategies for sustainable energy management. The results showcase that the proposed method significantly outperforms traditional approaches, achieving a 94% reduction in deployment time and a 98% decrease in memory usage through the use of standardized parametric models and plug-and-play IoT integration.

Applied SciencesVol. 14(24)
Democritus University of Thrace (GR), International Hellenic University (GR), Aristotle University of Thessaloniki (GR), 01 Pliroforiki (Greece) (GR), Sofia University "St. Kliment Ohridski" (BG), Chalmers University of Technology (SE), University of the Aegean (GR)
European Commission, Bulgarian National Science Fund, Horizon 2020 Framework Programme
Openalex Percentile: Top 8%
Smart Grid Energy Management
3.13
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