Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A Conceptual Framework For Blockchain and Ai-Driven Digital Twins For Predictive Operation and Maintenance
Jönköping University, School of Engineering, JTH, Construction Engineering and Lighting Science.ORCID iD: 0000-0001-7349-8557
Jönköping University, School of Engineering, JTH, Construction Engineering and Lighting Science.ORCID iD: 0000-0003-4288-9904
University of Turin, Torino, Italy.
Jönköping University, School of Engineering, JTH, Department of Computing.ORCID iD: 0000-0002-2161-7371
2023 (English)In: Proceedings of the 2023 European Conference on Computing in Construction and the 40th International CIB W78 Conference, European Council on Computing in Construction (EC3) , 2023Conference paper, Published paper (Refereed)
Abstract [en]

Digital Twins (DTs), enriched with Artificial Intelligence (AI) and Blockchain technology, promise a revolutionary breakthrough in smart asset management and predictive maintenance in the built environment. This study aims to portray a conceptual framework of Blockchain and AIbased DTs and outline its key characteristics, requirements, and system architecture by composing a functional model using IDEF0. Such an approach is expected to enhance predictive maintenance in building facilities, simplify the management and operation of smart built environments, and ultimately deliver valuable outcomes for facility operators, real estate practitioners, and end-users. 

Place, publisher, year, edition, pages
European Council on Computing in Construction (EC3) , 2023.
National Category
Construction Management
Identifiers
URN: urn:nbn:se:hj:diva-62964DOI: 10.35490/EC3.2023.219Scopus ID: 2-s2.0-85177229586OAI: oai:DiVA.org:hj-62964DiVA, id: diva2:1815705
Conference
2023 European Conference on Computing in Construction and Summer School 2023 CIB W78 40th International Conference and Charles M. Eastman PhD Award Heraklion 10 July 2023 through 12 July 2023
Available from: 2023-11-29 Created: 2023-11-29 Last updated: 2025-10-13Bibliographically approved
In thesis
1. Digital transformation for sustainable asset management: Integrating blockchain and AI with digital twins in building operations
Open this publication in new window or tab >>Digital transformation for sustainable asset management: Integrating blockchain and AI with digital twins in building operations
2024 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The swift evolution of building management systems necessitates the integration of advanced digital technologies to enhance operational efficiency, data security, and predictive maintenance. This thesis explores the potential and implementation challenges of integrating advanced technologies, namely, Blockchain, Digital Twins (DTs), Artificial Intelligence (AI), and the Internet of Things (IoT) within the smart built environment. Through a systematic review of current literature and empirical analysis, this research presents a comprehensive framework for these disruptive technologies' synergistic application, focusing on their impact on Asset Lifecycle Management (ALM).

Key findings demonstrate that Blockchain's immutable and transparent data handling capabilities significantly enhance the reliability and trustworthiness of DT data. The integration of AI with DTs facilitates predictive maintenance and optimization of building operations by providing real-time data analytics and automated decision-making processes. However, the study acknowledges substantial barriers, including the compatibility issues and the fragmented implementation of these technologies in the operation and maintenance (O&M) phase of building facilities throughout ALM.

To address these challenges, a conceptual framework and platform prototype were developed, showcasing practical solutions for integrating these technologies into Building Management Systems (BMS). The proposed framework emphasizes real-time data tracking, secure data storage, and automated maintenance task execution, leading to increased operational efficiency and cost savings.

This research contributes to the body of knowledge by providing a structured approach to integrating advanced technologies into BMS, highlighting the practical implications and sustainability benefits. The findings underscore the importance of stakeholder engagement and the need for continuous technological adaptation to realize the full potential of smart assetmanagement in the built environment.

Abstract [sv]

Den snabba utvecklingen av byggnadsförvaltningssystem kräver integration av avancerade digitala teknologier för att förbättra driftseffektivitet, datasäkerhet och prediktivt underhåll. Denna avhandling utforskar potentialen och implementeringsutmaningarna med att integrera avancerade teknologier, nämligen Blockchain, Digitala tvillingar (DTs), Artificiell Intelligens (AI) och Internet of Things (IoT) inom den smarta byggda miljön. Genom en systematisk översikt av aktuell litteratur och empirisk analys presenterar denna forskning ett omfattande ramverk för synergistisk tillämpning av dessa störande teknologier, med fokus på deras inverkan på Asset Lifecycle Management (ALM).

Huvudfynden visar att Blockchains oföränderliga och transparenta datahantering avsevärt förbättrar tillförlitligheten och trovärdigheten hos DT-data. Integrationen av AI med DTs underlättar prediktivt underhåll och optimering av byggnadsoperationer genom att tillhandahålla realtidsdataanalys och automatiserade beslutsprocesser. Studien erkänner dock betydande hinder, inklusive kompatibilitetsproblem och fragmenterad implementering av dessa teknologier i drift- och underhållsfasen (O&M) av byggnadsanläggningar under ALM.

För att ta itu med dessa utmaningar utvecklades ett konceptuellt ramverk och en prototypplattform som visar praktiska lösningar för att integrera dessa teknologier i fastighetsautomationssystem (BMS). Det föreslagna ramverket betonar spårning av data i realtid, säker datalagring och automatiserad utförande av underhållsuppgifter, vilket leder till ökad driftseffektivitet och kostnadsbesparingar.

Denna forskning bidrar till kunskapsbasen genom att tillhandahålla ett strukturerat tillvägagångssätt för att integrera avancerade teknologier i BMS, med fokus på de praktiska implikationerna och hållbarhetsfördelarna. Resultaten understryker vikten av intressentengagemang och behovet av kontinuerlig teknologianpassning för att realisera hela potentialen av smarttillgångshantering i den byggda miljön.

Place, publisher, year, edition, pages
Jönköping: Jönköping University, School of Engineering, 2024. p. 79
Series
JTH Dissertation Series ; 091
Keywords
Smart buildings, Digitalization, Asset Management, Artificial Intelligence, Digital Twin, Blockchain, Building Operation and Maintenance
National Category
Construction Management Computer Sciences
Identifiers
urn:nbn:se:hj:diva-66762 (URN)978-91-89785-15-1 (ISBN)978-91-89785-16-8 (ISBN)
Presentation
2024-10-24, E1405 (Gjuterisalen), Tekniska Högskolan, Jönköping, 10:00 (English)
Opponent
Supervisors
Available from: 2024-12-16 Created: 2024-12-16 Last updated: 2025-10-13Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopusFulltext

Authority records

Sadri, HabibYitmen, IbrahimWestphal, Florian

Search in DiVA

By author/editor
Sadri, HabibYitmen, IbrahimWestphal, Florian
By organisation
JTH, Construction Engineering and Lighting ScienceJTH, Department of Computing
Construction Management

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 255 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf