Leveraging Power BI as a Front-End Digital Twin for Cooperative Data-Driven Visualisation

Meinhardt Thorlund Haahr; Odin Iversen; Raphael Peter Harrow-Hodgkinson

doi:10.1007/978-3-032-06952-8_23

Leveraging Power BI as a Front-End Digital Twin for Cooperative Data-Driven Visualisation

Norwegian University of Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution to proceeding › peer-review

Abstract

The Architecture, Engineering, Construction, and Operation (AEC-O) industry is undergoing a digital transformation, particularly in the operation phase of buildings, where effective tools for real-time monitoring and performance analysis are still lacking. Digital twins offer an integrated approach to combining real-time sensor data with analytics, yet current implementations are often complex and proprietary, limiting accessibility for multidisciplinary stakeholders. This study explores the potential of Power BI as a cooperative and accessible front-end platform for digital twins that supports building performance visualisation and data-driven decision-making.

Unlike traditional tools and static reporting, Power BI enables dynamic exploration of real-time and historical data via interactive dashboards. These dashboards allow end-users to filter, drill down, and interact, while cloud-based features support multi-user collaboration and continuous updates.

Two digital twins were developed for buildings in Norway and Spain with IoT sensors monitoring environmental parameters. This paper presents the system architecture of a developed artefact and demonstrates its deployment in these two cases. Furthermore, the artefact’s capability to provide insights into building performance is evaluated. By integrating data-driven insights into an accessible visualisation environment, this work contributes a practical digital twin solution tailored to the needs of the AEC-O domain.

Original language	English
Title of host publication	Cooperative Design, Visualization, and Engineering - 22nd International Conference, CDVE 2025, Proceedings : 22nd International Conference, CDVE 2025, Bangkok, Thailand, October 19-22, 2025, Proceedings
Editors	Yuhua Luo
Number of pages	11
Publisher	Springer
Publication date	2026
Pages	228-238
ISBN (Print)	978-3-032-06951-1
ISBN (Electronic)	978-3-032-06952-8
DOIs	https://doi.org/10.1007/978-3-032-06952-8_23
Publication status	Published - 2026
Event	The 22nd International Conference on Cooperative Design, Visualization and Engineeting (CDVE 2025) - Berkeley Hotel Pratunam, 559 Ratchaprarop Road, Makkasan, Bangkok, Thailand Duration: 19 Oct 2025 → 22 Oct 2025 Conference number: 22 https://www.cdve.org/program.html

Conference

Conference	The 22nd International Conference on Cooperative Design, Visualization and Engineeting (CDVE 2025)
Number	22
Location	Berkeley Hotel Pratunam, 559 Ratchaprarop Road, Makkasan
Country/Territory	Thailand
City	Bangkok
Period	19/10/25 → 22/10/25
Internet address	https://www.cdve.org/program.html

Series	Lecture Notes in Computer Science
Volume	16092
ISSN	0302-9743

Keywords

technology, engineering and IT
AEC-O
Data-Driven
Digital Twin
IoT Sensor
Visualisation

Access to Document

10.1007/978-3-032-06952-8_23

Cite this

Haahr, M. T., Iversen, O., & Harrow-Hodgkinson, R. P. (2026). Leveraging Power BI as a Front-End Digital Twin for Cooperative Data-Driven Visualisation. In Y. Luo (Ed.), Cooperative Design, Visualization, and Engineering - 22nd International Conference, CDVE 2025, Proceedings: 22nd International Conference, CDVE 2025, Bangkok, Thailand, October 19-22, 2025, Proceedings (pp. 228-238). Springer. https://doi.org/10.1007/978-3-032-06952-8_23

Haahr, Meinhardt Thorlund ; Iversen, Odin ; Harrow-Hodgkinson, Raphael Peter. / Leveraging Power BI as a Front-End Digital Twin for Cooperative Data-Driven Visualisation. Cooperative Design, Visualization, and Engineering - 22nd International Conference, CDVE 2025, Proceedings: 22nd International Conference, CDVE 2025, Bangkok, Thailand, October 19-22, 2025, Proceedings. editor / Yuhua Luo. Springer, 2026. pp. 228-238 (Lecture Notes in Computer Science, Vol. 16092).

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title = "Leveraging Power BI as a Front-End Digital Twin for Cooperative Data-Driven Visualisation",

abstract = "The Architecture, Engineering, Construction, and Operation (AEC-O) industry is undergoing a digital transformation, particularly in the operation phase of buildings, where effective tools for real-time monitoring and performance analysis are still lacking. Digital twins offer an integrated approach to combining real-time sensor data with analytics, yet current implementations are often complex and proprietary, limiting accessibility for multidisciplinary stakeholders. This study explores the potential of Power BI as a cooperative and accessible front-end platform for digital twins that supports building performance visualisation and data-driven decision-making. Unlike traditional tools and static reporting, Power BI enables dynamic exploration of real-time and historical data via interactive dashboards. These dashboards allow end-users to filter, drill down, and interact, while cloud-based features support multi-user collaboration and continuous updates. Two digital twins were developed for buildings in Norway and Spain with IoT sensors monitoring environmental parameters. This paper presents the system architecture of a developed artefact and demonstrates its deployment in these two cases. Furthermore, the artefact{\textquoteright}s capability to provide insights into building performance is evaluated. By integrating data-driven insights into an accessible visualisation environment, this work contributes a practical digital twin solution tailored to the needs of the AEC-O domain.",

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Haahr, MT, Iversen, O & Harrow-Hodgkinson, RP 2026, Leveraging Power BI as a Front-End Digital Twin for Cooperative Data-Driven Visualisation. in Y Luo (ed.), Cooperative Design, Visualization, and Engineering - 22nd International Conference, CDVE 2025, Proceedings: 22nd International Conference, CDVE 2025, Bangkok, Thailand, October 19-22, 2025, Proceedings. Springer, Lecture Notes in Computer Science, vol. 16092, pp. 228-238, The 22nd International Conference on Cooperative Design, Visualization and Engineeting (CDVE 2025), Bangkok, Thailand, 19/10/25. https://doi.org/10.1007/978-3-032-06952-8_23

Leveraging Power BI as a Front-End Digital Twin for Cooperative Data-Driven Visualisation. / Haahr, Meinhardt Thorlund; Iversen, Odin; Harrow-Hodgkinson, Raphael Peter.
Cooperative Design, Visualization, and Engineering - 22nd International Conference, CDVE 2025, Proceedings: 22nd International Conference, CDVE 2025, Bangkok, Thailand, October 19-22, 2025, Proceedings. ed. / Yuhua Luo. Springer, 2026. p. 228-238 (Lecture Notes in Computer Science, Vol. 16092).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution to proceeding › peer-review

TY - GEN

T1 - Leveraging Power BI as a Front-End Digital Twin for Cooperative Data-Driven Visualisation

AU - Haahr, Meinhardt Thorlund

AU - Iversen, Odin

AU - Harrow-Hodgkinson, Raphael Peter

N1 - Conference code: 22

PY - 2026

Y1 - 2026

N2 - The Architecture, Engineering, Construction, and Operation (AEC-O) industry is undergoing a digital transformation, particularly in the operation phase of buildings, where effective tools for real-time monitoring and performance analysis are still lacking. Digital twins offer an integrated approach to combining real-time sensor data with analytics, yet current implementations are often complex and proprietary, limiting accessibility for multidisciplinary stakeholders. This study explores the potential of Power BI as a cooperative and accessible front-end platform for digital twins that supports building performance visualisation and data-driven decision-making. Unlike traditional tools and static reporting, Power BI enables dynamic exploration of real-time and historical data via interactive dashboards. These dashboards allow end-users to filter, drill down, and interact, while cloud-based features support multi-user collaboration and continuous updates. Two digital twins were developed for buildings in Norway and Spain with IoT sensors monitoring environmental parameters. This paper presents the system architecture of a developed artefact and demonstrates its deployment in these two cases. Furthermore, the artefact’s capability to provide insights into building performance is evaluated. By integrating data-driven insights into an accessible visualisation environment, this work contributes a practical digital twin solution tailored to the needs of the AEC-O domain.

AB - The Architecture, Engineering, Construction, and Operation (AEC-O) industry is undergoing a digital transformation, particularly in the operation phase of buildings, where effective tools for real-time monitoring and performance analysis are still lacking. Digital twins offer an integrated approach to combining real-time sensor data with analytics, yet current implementations are often complex and proprietary, limiting accessibility for multidisciplinary stakeholders. This study explores the potential of Power BI as a cooperative and accessible front-end platform for digital twins that supports building performance visualisation and data-driven decision-making. Unlike traditional tools and static reporting, Power BI enables dynamic exploration of real-time and historical data via interactive dashboards. These dashboards allow end-users to filter, drill down, and interact, while cloud-based features support multi-user collaboration and continuous updates. Two digital twins were developed for buildings in Norway and Spain with IoT sensors monitoring environmental parameters. This paper presents the system architecture of a developed artefact and demonstrates its deployment in these two cases. Furthermore, the artefact’s capability to provide insights into building performance is evaluated. By integrating data-driven insights into an accessible visualisation environment, this work contributes a practical digital twin solution tailored to the needs of the AEC-O domain.

KW - technology, engineering and IT

KW - AEC-O

KW - Data-Driven

KW - Digital Twin

KW - IoT Sensor

KW - Visualisation

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U2 - 10.1007/978-3-032-06952-8_23

DO - 10.1007/978-3-032-06952-8_23

M3 - Conference contribution to proceeding

SN - 978-3-032-06951-1

T3 - Lecture Notes in Computer Science

SP - 228

EP - 238

BT - Cooperative Design, Visualization, and Engineering - 22nd International Conference, CDVE 2025, Proceedings

A2 - Luo, Yuhua

PB - Springer

T2 - The 22nd International Conference on Cooperative Design, Visualization and Engineeting (CDVE 2025)

Y2 - 19 October 2025 through 22 October 2025

ER -

Haahr MT, Iversen O, Harrow-Hodgkinson RP. Leveraging Power BI as a Front-End Digital Twin for Cooperative Data-Driven Visualisation. In Luo Y, editor, Cooperative Design, Visualization, and Engineering - 22nd International Conference, CDVE 2025, Proceedings: 22nd International Conference, CDVE 2025, Bangkok, Thailand, October 19-22, 2025, Proceedings. Springer. 2026. p. 228-238. (Lecture Notes in Computer Science, Vol. 16092). doi: 10.1007/978-3-032-06952-8_23

Leveraging Power BI as a Front-End Digital Twin for Cooperative Data-Driven Visualisation

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

DigiLab/BE: DigitalLab for the Built Environment: An Integrated Approach for Upgrading Digital Skills in Technical Education

The 22nd International Conference on Cooperative Design, Visualization and Engineeting (CDVE 2025)

Digitale tvillinger i praksis: Erfaringer fra DigiLab-projektet - (Workshop)

Cite this

Leveraging Power BI as a Front-End Digital Twin for Cooperative Data-Driven Visualisation

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Projects

DigiLab/BE: DigitalLab for the Built Environment: An Integrated Approach for Upgrading Digital Skills in Technical Education

Activities

The 22nd International Conference on Cooperative Design, Visualization and Engineeting (CDVE 2025)

Digitale tvillinger i praksis​: Erfaringer fra DigiLab-projektet ​- (Workshop)

Cite this

Digitale tvillinger i praksis: Erfaringer fra DigiLab-projektet - (Workshop)