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Optimizing Carbon Footprint & Energy Performance for the Sustainability of Historic Buildings using Knowledge Graphs & Digital Twins

Authors: Vassiliades, Alexandros; Karageorgiadis, Anastasios I.; Batziou, Elissavet; Diplaris, Sotiris; Stathopoulos, Evangelos A.; Dourvas, Nikolaos; Ioannidis, Konstantinos; +2 Authors

Optimizing Carbon Footprint & Energy Performance for the Sustainability of Historic Buildings using Knowledge Graphs & Digital Twins

Abstract

Cultural heritage preservation is crucial for climate resilience and sustainable development, requiring innovative tools, materials, and adaptive renovation to mitigate climate risks, reduce emissions, and enhance sustainability in line with the EU Green Deal and UN Sustainable Development Goals. This paper presents ongoing work integrating Knowledge Graphs, Digital Twins, and Building Information Modeling (BIM) to optimize the carbon footprint and energy performance of historic buildings through innovative restoration materials, energy harvesting technologies, and socially-driven approaches, aligning with net-zero-carbon goals. We propose a pipeline where a Digital Twin, incorporating a BIM model, simulates a historic building’s virtual representation to evaluate how different materials impact energy consumption and sustainability. The Knowledge Graph stores historical, real-time (sensor-based), and predicted weather data, enabling the Digital Twin to assess weather-driven energy performance variations and determine optimal material choices. As part of the EU-funded SINCERE project, this system provides a data-driven decision-making framework for stakeholders, supporting restoration, operation, and long-term sustainability planning for Built Cultural Heritage.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average