Dynamic EU building stock knowledge hub

Projektinformationen

BUILTHUB

ID Finanzhilfevereinbarung: 957026

DOI

10.3030/957026

Projekt abgeschlossen

EK-Unterschriftsdatum 27 Juli 2020

Startdatum 1 Oktober 2020

Enddatum 30 September 2024

Finanziert unter

• SOCIETAL CHALLENGES - Secure, clean and efficient energy

Gesamtkosten

€ 2 197 088,75

EU-Beitrag

€ 2 197 088,75

Koordiniert durch

ACCADEMIA EUROPEA DI BOLZANO
Italy

CORDIS bietet Links zu öffentlichen Ergebnissen und Veröffentlichungen von HORIZONT-Projekten.

Links zu Ergebnissen und Veröffentlichungen von RP7-Projekten sowie Links zu einigen Typen spezifischer Ergebnisse wie Datensätzen und Software werden dynamisch von OpenAIRE abgerufen.

Leistungen

Other (3)

Project Flyer
Promotional Material
Matrix, describing the available datasets and main data sources and type

Matrix, describing the available datasets, as well as main sources, data types, data classes, interlink between datasets and etc. (draft M12, M18)

Websites, patent fillings, videos etc. (3)

Platform demo video
Project website, visual identity and templates
Project Introduction video

Documents, reports (14)

Report on relationships of stakeholder needs and requirements

Report on relationships of stakeholder needs and their technical requirements

Circular economy approach for contributing to bld stock decarbonisation

Circular economy approach principle for contributing to building stock decarbonisation, (draft M24)

Building stock progress monitoring report

Building stock progress monitoring report with a first pilot issue by M36

Building sector indicators, definition, calculation, representation

Building sector indicators, their detailed definition, the necessary data to provide them, main datasets sources that should be used, possible benchmarking threshold values and possible definition of the graphical presentation (draft M12, 24)

Final Communication, Dissemination and Exploitation Tracker
Stakeholder mapping

Stakeholder mapping: infographic and shot report summarizing approach and lessons learnt

Report on training programmes and pilot initiatives

Report on training programmes and pilot initiatives by ambassador group (draft M24)

Functionalities of the BuiltHub platform and provided services

Functionalities of the BuiltHub platform and provided services (draft M12)

Final stakeholder engagement report

Final stakeholder engagement report including achievement of workshops, pioneering use, stakeholder dialogues (draft M30)

Report on data visualization

D4.5 Report on data visualization (draft M18, M30)

Guidelines to enhance the capacity of policymakers & stakeholders

Guidelines to enhance the capacity of local, national, and EU policymakers & stakeholders

Methodology on quality assurance

Methodology on quality assurance (draft M18)

Inventory structure and main feature and datasets

Inventory structure and main feature and datasets (draft M6)

Roadmap towards dynamic and automated bld. data collection

Roadmap towards dynamic and automated building data collection, eventually leading to a live picture of the building stock, (annual draft M12, M24, M36)

Veröffentlichungen

Conference proceedings (1)

Building Stock Datasets Analysis in the BuiltHub Project

Autoren: Carla Rodríguez Alonso, Víctor Iván Serna González, Gema Hernández Moral
Veröffentlicht in: 2023 14th International Conference on Information, Intelligence, Systems & Applications (IISA), 2024, Seite(n) 1-8
Herausgeber: IEEE
DOI: 10.1109/iisa59645.2023.10345874

Monographic books (1)

European Building Stock Analysis

Autoren: Aleksandr Gevorgian, Simon Pezzutto, Stefano Zambotti, Silvia Croce, Ulrich Filippi Oberegger, Roberto Lollini, Lukas Kranzl, Andreas Müller
Veröffentlicht in: 2021, ISBN 978-88-98857-68-5
Herausgeber: Eurac

Peer reviewed articles (7)

Evaluating the indoor radon concentrations in the Swedish building stock using statistical and machine learning

Autoren: Pei-Yu Wu, Tim Johansson, Mikael Mangold, Claes Sandels, Kristina Mjörnell
Veröffentlicht in: Journal of Physics: Conference Series, Ausgabe 2654, 2023, Seite(n) 012086, ISSN 1742-6588
Herausgeber: Institute of Physics
DOI: 10.1088/1742-6596/2654/1/012086

Predicting the presence of hazardous materials in buildings using machine learning

Autoren: Pei-Yu Wu, Claes Sandels, Kristina Mjörnell, Mikael Mangold, Tim Johansson
Veröffentlicht in: Building and Environment, Ausgabe 213, 2023, Seite(n) 108894, ISSN 0360-1323
Herausgeber: Pergamon Press Ltd.
DOI: 10.1016/j.buildenv.2022.108894

Assessment of Building Materials in the European Residential Building Stock: An Analysis at EU27 Level

Autoren: Claudio Zandonella Callegher; Gianluca Grazieschi; Eric Wilczynski ; Ulrich Filippi Oberegger; Simon Pezzutto
Veröffentlicht in: Sustainability, Ausgabe Sustainability 2023, 15(11), 8840, 2023, ISSN 2071-1050
Herausgeber: MDPI Open Access Publishing
DOI: 10.3390/su15118840

Modeling Artificial Neural Networks to Predict Asbestos-containing Materials in Residential Buildings

Autoren: Pei-Yu Wu, Mikael Mangold, Claes Sandels, Tim Johansson, Kristina Mjörnell
Veröffentlicht in: IOP Conference Series: Earth and Environmental Science, Ausgabe 1122, 2022, Seite(n) 012050, ISSN 1755-1307
Herausgeber: IOPScience
DOI: 10.1088/1755-1315/1122/1/012050

Integration of datasets to provide insights about households’ natural gas expenditure as trigger to building stock decarbonisation

Autoren: Iná E.N. Maia, R.M. Moraes, R.T. Almeida, L. Kranzl, A. Müller, F. Schipfer
Veröffentlicht in: Heliyon, Ausgabe 9, 2024, Seite(n) e14922, ISSN 2405-8440
Herausgeber: Heliyon
DOI: 10.1016/j.heliyon.2023.e14922

Machine learning models for the prediction of polychlorinated biphenyls and asbestos materials in buildings, Resources, Conservation, and Recycling (2023)

Autoren: Pei-Yu Wu, Claes Sandels, Tim Johansson, Mikael Mangold, Kristina Mjörnell,
Veröffentlicht in: Resources, Conservation and Recycling, Ausgabe Resources, Conservation and Recycling Volume 199, December 2023, 107253, 2023, ISSN 0921-3449
Herausgeber: Elsevier BV
DOI: 10.1016/j.resconrec.2023.107253

Estimating the probability distributions of radioactive concrete in the building stock using Bayesian networks

Autoren: Pei-Yu Wu, Tim Johansson, Mikael Mangold, Claes Sandels, Kristina Mjörnell
Veröffentlicht in: Expert Systems with Applications, Ausgabe 222, 2024, Seite(n) 119812, ISSN 0957-4174
Herausgeber: Pergamon Press Ltd.
DOI: 10.1016/j.eswa.2023.119812