Semantic Data-Driven Models to Improve Energy Efficiency in Buildings and Cities

Títol traduït de la contribució: Semantic Data-Driven Models to Improve Energy Efficiency in Buildings and Cities

Producció científica: Capítol de llibreCapítol

Resum

The assessment of building energy performance requires data from multiple domains (energy, architecture, planning, economy) and scales (building, district, city) to be processed with a diversity of applications used by experts from various fields. In order to properly assess the performance of the building stock, and to develop and apply the most effective energy efficiency measures, it is necessary to adopt a comprehensive, holistic approach. In this chapter, three research projects are presented which apply Semantic Web technologies to create energy data models from multiple data sources and domains in order to support decision making in energy efficient building renovation projects: SEMANCO, OptEEmAL, and OPTIMUS. A final reflection on the results achieved in these projects and their links to ongoing research on digital twins is presented.
Títol traduït de la contribucióSemantic Data-Driven Models to Improve Energy Efficiency in Buildings and Cities
Idioma originalAnglès
Títol de la publicacióHandbook of Research on Developing Smart Cities Based on Digital Twins
EditorsMatteo Del Giudice, Anna Osello
EditorIGI Global http://www.igi-global.com/
Pàgines515-539
Nombre de pàgines24
ISBN (imprès) 9781799870913
DOIs
Estat de la publicacióPublicada - 1 de gen. 2021

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