Energy-data-related digital twin for office building and data centre complex

Lotta Kannari; Kalevi Piira; Henri Biström; Terttu Vainio

doi:10.1109/DCIS55711.2022.9970040

Energy-data-related digital twin for office building and data centre complex

Lotta Kannari
, Kalevi Piira
, Henri Biström
, Terttu Vainio

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

11 Citations (Scopus)

Abstract

This paper describes the developed digital twin of an office building and data centre complex. The definition of how a digital twin used here is that it looks the same and behaves in the same way as the real counterpart. This is implemented with integration of the Building Information Model (BIM), energy measurements and predictions of energy consumptions of the building with neural networks. A 3D viewer is used to enable the visual analysis of the energy consumption of different parts of the building.

Original language	English
Title of host publication	Proceedings of the 37th Conference on Design of Circuits and Integrated Circuits, DCIS 2022
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	1-5
Number of pages	5
ISBN (Electronic)	978-1-6654-5950-1
DOIs	https://doi.org/10.1109/DCIS55711.2022.9970040
Publication status	Published - 8 Dec 2022
MoE publication type	A4 Article in a conference publication
Event	37th Conference on Design of Circuits and Integrated Circuits, DCIS 2022 - Pamplona, Spain Duration: 16 Nov 2022 → 18 Nov 2022

Conference

Conference	37th Conference on Design of Circuits and Integrated Circuits, DCIS 2022
Country/Territory	Spain
City	Pamplona
Period	16/11/22 → 18/11/22

Funding

The work behind this article have been made possible by the EU Stardust Smart City project, which has received funding from the European Union s Horizon 2020 research and Innovation programme under grant agreement N 774094 and CityIoT (Future operator independent data integration platform), which is funded by European Regional Development Fund.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

ANN model
BIM
BIM model server
data centre
data platform
deep learning
digital twin
energy consumption
energy data transfer
machine learning
prosumer
Stardust
virtual model

Access to Document

10.1109/DCIS55711.2022.9970040

Cite this

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title = "Energy-data-related digital twin for office building and data centre complex",

abstract = "This paper describes the developed digital twin of an office building and data centre complex. The definition of how a digital twin used here is that it looks the same and behaves in the same way as the real counterpart. This is implemented with integration of the Building Information Model (BIM), energy measurements and predictions of energy consumptions of the building with neural networks. A 3D viewer is used to enable the visual analysis of the energy consumption of different parts of the building.",

keywords = "ANN model, BIM, BIM model server, data centre, data platform, deep learning, digital twin, energy consumption, energy data transfer, machine learning, prosumer, Stardust, virtual model",

author = "Lotta Kannari and Kalevi Piira and Henri Bistr{\"o}m and Terttu Vainio",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 37th Conference on Design of Circuits and Integrated Circuits, DCIS 2022 ; Conference date: 16-11-2022 Through 18-11-2022",

year = "2022",

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doi = "10.1109/DCIS55711.2022.9970040",

language = "English",

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booktitle = "Proceedings of the 37th Conference on Design of Circuits and Integrated Circuits, DCIS 2022",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

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}

Kannari, L, Piira, K , Biström, H & Vainio, T 2022, Energy-data-related digital twin for office building and data centre complex. in Proceedings of the 37th Conference on Design of Circuits and Integrated Circuits, DCIS 2022. IEEE Institute of Electrical and Electronic Engineers, pp. 1-5, 37th Conference on Design of Circuits and Integrated Circuits, DCIS 2022, Pamplona, Spain, 16/11/22. https://doi.org/10.1109/DCIS55711.2022.9970040

Energy-data-related digital twin for office building and data centre complex. / Kannari, Lotta; Piira, Kalevi ; Biström, Henri et al.
Proceedings of the 37th Conference on Design of Circuits and Integrated Circuits, DCIS 2022. IEEE Institute of Electrical and Electronic Engineers, 2022. p. 1-5.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Energy-data-related digital twin for office building and data centre complex

AU - Kannari, Lotta

AU - Piira, Kalevi

AU - Biström, Henri

AU - Vainio, Terttu

PY - 2022/12/8

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N2 - This paper describes the developed digital twin of an office building and data centre complex. The definition of how a digital twin used here is that it looks the same and behaves in the same way as the real counterpart. This is implemented with integration of the Building Information Model (BIM), energy measurements and predictions of energy consumptions of the building with neural networks. A 3D viewer is used to enable the visual analysis of the energy consumption of different parts of the building.

AB - This paper describes the developed digital twin of an office building and data centre complex. The definition of how a digital twin used here is that it looks the same and behaves in the same way as the real counterpart. This is implemented with integration of the Building Information Model (BIM), energy measurements and predictions of energy consumptions of the building with neural networks. A 3D viewer is used to enable the visual analysis of the energy consumption of different parts of the building.

KW - ANN model

KW - BIM

KW - BIM model server

KW - data centre

KW - data platform

KW - deep learning

KW - digital twin

KW - energy consumption

KW - energy data transfer

KW - machine learning

KW - prosumer

KW - Stardust

KW - virtual model

UR - https://www.scopus.com/pages/publications/85145438469

U2 - 10.1109/DCIS55711.2022.9970040

DO - 10.1109/DCIS55711.2022.9970040

M3 - Conference article in proceedings

SP - 1

EP - 5

BT - Proceedings of the 37th Conference on Design of Circuits and Integrated Circuits, DCIS 2022

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - 37th Conference on Design of Circuits and Integrated Circuits, DCIS 2022

Y2 - 16 November 2022 through 18 November 2022

ER -

Energy-data-related digital twin for office building and data centre complex

Abstract

Conference

Funding

UN SDGs

Keywords

Access to Document

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Cite this