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

Applied Sciences

20763417 (eISSN)

Vol. 14 24 11834

Ämneskategorier (SSIF 2011)

Energiteknik

Datavetenskap (datalogi)

DOI

10.3390/app142411834

Mer information

Senast uppdaterat

2025-01-10