CREATING DIGITAL TWINS OF SMART BUILDINGS ON THE AZURE DIGITAL TWINS PLATFORM

Authors

  • A.V. Kalaida Харківський національний університет міського господарства імені О.М. Бекетова
  • M.P. Pan Харківський національний університет міського господарства імені О.М. Бекетова

DOI:

https://doi.org/10.33042/2522-1809-2024-6-187-2-7

Keywords:

digital twin, pipeline, ontology

Abstract

The relevance of developing digital twins of smart buildings on the Azure Digital Twins platform is shaped by numerous factors reflecting contemporary trends in the construction industry and property management. The escalating demand for resource efficiency, optimizing energy usage, and augmenting user comfort are propelling the shift towards intelligent building systems. Azure Digital Twins presents remarkable capabilities for crafting digital models of buildings and their virtual representation. This enables the integration of innovative technologies like the Internet of Things (IoT), artificial intelligence, and data analytics to enhance building management. A key contemporary advantage lies in the real-time tracking of a building's systems, encompassing energy consumption, security, ventilation, and various facets. This facilitates prompt responses to ongoing issues and proactively prevents malfunctions.
In the context of escalating demands for sustainable construction and energy-efficient management, creating digital twins of smart buildings on Azure Digital Twins becomes a necessary step towards achieving high productivity, cost reduction, and fostering comfortable living and working environments. The creation of digital twins for smart buildings on the Azure Digital Twins platform holds significance in municipal infrastructure management and resource optimization. This encompasses energy management, water supply, waste management, and other aspects of municipal services. In the broader context of overall IT development, creating digital twins of smart buildings reflects a powerful driver towards societal digital transformation. Integrating IoT, data analytics, and artificial intelligence into municipal infrastructure management heightens efficiency, rendering management processes more flexible and adaptive to change.
Information technologies based on digital twins of smart buildings stimulate the advancement of intelligent cities, elevating residents' comfort and quality of life. The ontological approach allows for constructing models that not only accurately reflect physical object characteristics but also ensure a structured understanding of relationships between different elements. This enables efficient data analysis, prediction of potential changes, and real-time responsiveness.
The application of ontologies in constructing digital twins emerges as a pivotal stage in IoT and smart technology industry evolution. It not only aids in virtual object modeling but also unlocks doors for innovative solutions in data analytics, forecasting, and management process automation.

Author Biographies

A.V. Kalaida, Харківський національний університет міського господарства імені О.М. Бекетова

магістр зі спеціальності 122 Комп’ютерні науки

M.P. Pan, Харківський національний університет міського господарства імені О.М. Бекетова

кандидат технічних наук, доцент кафедри комп’ютерних наук та інформаційних технологій

References

Juntong Yun, Gongfa Li, Du Jiang, Manman Xu, Feng Xiang, Li Huang, Guozhang Jiang, Xin Liu, Yuanmin Xie, Bo Tao, Zifan Fang (2023) Digital twin model construction of robot and multi-object under stacking environment for grasping planning. Applied Soft Computing Volume 149, Part A, December 2023, 111005, https://doi.org/10.1016/j.asoc.2023.111005.

Walter Lohman, Hans Cornelissen, Jeroen Borst, Ralph Klerkx, Yashar Araghi, Erwin Walraven (2023) Building digital twins of cities using the Inter Model Broker framework. Future Generation Computer Systems Volume 148, November 2023, Pages 501-513, https://doi.org/10.1016/j.future.2023.06.024.

Hang Tian, Haoran Zhao, Haoran Li, Xiaoli Huang, Xiaoyi Qian, Xu Huang (2023) Digital twins of multiple energy networks based on real-time simulation using holomorphic embedding method, Part II: Data-driven simulation. International Journal of Electrical Power & Energy Systems Volume 153, November 2023, 109325, https://doi.org/10.1016/j.ijepes.2023.109325.

Dongjie Zhang, Zhifeng Liu, Fuping Li, Yongsheng Zhao, Caixia Zhang, Xin Li, Yueze Zhang (2023) The rapid construction method of the digital twin polymorphic model for discrete manufacturing workshop. Robotics and Computer-Integrated Manufacturing Volume 84, December 2023, 102600, https://doi.org/10.1016/j.rcim.2023.102600.

Xiaolang Yang, Xuemei Liu, Heng Zhang, Ling Fu, Yanbin Yu (2023) Meta-model-based shop-floor digital twin architecture, modeling and application. Robotics and Computer-Integrated Manufacturing Volume 84, December 2023, 102595, https://doi.org/10.1016/j.rcim.2023.102595.

Ahmed Al-Ashaab, Nik Fadilah, Faiz Djafri, Sai Nikhil Kumar Jaini, Glyn Fargher b, Hugo Chester (2023) Development of Digital Twin of a Compact Bulk Feeder to Optimise its Functionality. Procedia Computer Science Volume 217, 2023, Pages 536-542, https://doi.org/10.1016/j.procs.2022.12.249.

Maxwell Toothman, Birgit Braun, Scott J. Bury, James Moyne, Dawn M. Tilbury, Yixin Ye, Kira Barton (2023) A digital twin framework for prognostics and health management. Computers in Industry Volume 150, September 2023, 103948, https://doi.org/10.1016/j.compind.2023.103948.

Brian Hickey, Dr Carine Gachon, Dr John Cosgrove (2023) Digital Twin – A Tool for Project Management in Manufacturing. Procedia Computer Science Volume 217, 2023, Pages 720-727, https://doi.org/10.1016/j.procs.2022.12.268.

Raymon van Dinter, Bedir Tekinerdogan, Cagatay Catal (2022) Predictive maintenance using digital twins: A systematic literature review. Information and Software Technology Volume 151, November 2022, 107008, https://doi.org/10.1016/j.infsof.2022.107008.

Zhihan Lv, Shuxuan Xie, Yuxi Li, M. Shamim Hossain, Abdulmotaleb El Saddik (2022) Building the metaverse using digital twins at all scales,states, and relations. Virtual Reality & Intelligent Hardware Volume 4, Issue 6, December 2022, Pages 459-470, https://doi.org/10.1016/j.vrih.2022.06.005.

RealEstateCore Consortium: Karl Hammar, Erik Wallin, Per Karlberg, Peter Hartlev, Joakim Eriksson November 6 2020.

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Published

2024-12-17

How to Cite

Kalaida, A., & Pan, M. (2024). CREATING DIGITAL TWINS OF SMART BUILDINGS ON THE AZURE DIGITAL TWINS PLATFORM. Municipal Economy of Cities, 6(187), 2–7. https://doi.org/10.33042/2522-1809-2024-6-187-2-7

Issue

Vol. 6 No. 187 (2024)

Section

статьи

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