A Scalable and User-Friendly Framework Integrating IoT and Digital Twins for Home Energy Management Systems
Artikel i vetenskaplig tidskrift, 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
Författare
Myrto Stogia
Panepistimion Aegaeou
Vasilis Naserentin
Aristotelio Panepistimio Thessalonikis
Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik
Asimina Dimara
Democritus University of Thrace
Panepistimion Aegaeou
Orfeas Eleftheriou
Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik
Code-Flow
Ioannis Tzitzios
Democritus University of Thrace
Christoforos Papaioannou
International Hellenic University (IHU)
Mariya Pantusheva
Sofijski universitet
Alexios Papaioannou
Democritus University of Thrace
Georgios Spaias
Student vid Chalmers
Aristotelio Panepistimio Thessalonikis
Christos Nikolaos Anagnostopoulos
Panepistimion Aegaeou
Anders Logg
Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik
Stelios Krinidis
International Hellenic University (IHU)
Democritus University of Thrace
Publicerad i
Applied Sciences
20763417 (eISSN)
Vol. 14 Nummer/häfte 24 art. nr 11834Kategorisering
Ämneskategorier (SSIF 2011)
Energiteknik
Datavetenskap (datalogi)
Identifikatorer
DOI
10.3390/app142411834