A Scalable and User-Friendly Framework Integrating IoT and Digital Twins for Home Energy Management Systems
Journal article, 2024
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.
real-time monitoring
digital twin
internet of things
IoT architecture
home energy management systems
Author
Myrto Stogia
University of the Aegean
Vasilis Naserentin
Aristotle University of Thessaloniki
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
Asimina Dimara
Democritus University of Thrace
University of the Aegean
Orfeas Eleftheriou
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
Code-Flow
Ioannis Tzitzios
Democritus University of Thrace
Christoforos Papaioannou
International Hellenic University (IHU)
Mariya Pantusheva
Sofia University
Alexios Papaioannou
Democritus University of Thrace
Georgios Spaias
Student at Chalmers
Aristotle University of Thessaloniki
Christos Nikolaos Anagnostopoulos
University of the Aegean
Anders Logg
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
Stelios Krinidis
International Hellenic University (IHU)
Democritus University of Thrace
Applied Sciences
20763417 (eISSN)
Vol. 14 24 11834Subject Categories (SSIF 2011)
Energy Engineering
Computer Science
DOI
10.3390/app142411834