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Digital twin of buildings and occupants for emergency evacuation: Framework, technologies, applications and trends.

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Title: Digital twin of buildings and occupants for emergency evacuation: Framework, technologies, applications and trends.
Authors: Lin, Jia-Rui1,2 (AUTHOR) lin611@tsinghua.edu.cn, Chen, Ke-Yin1 (AUTHOR) chenky22@mails.tsinghua.edu.cn, Song, Sheng-Yu1 (AUTHOR), Cai, Yun-Hong1 (AUTHOR), Pan, Peng1,2 (AUTHOR) panpeng@tsinghua.edu.cn, Deng, Yi-Chuan3 (AUTHOR)
Source: Advanced Engineering Informatics. Jul2025, Vol. 66, pN.PAG-N.PAG. 1p.
Subjects: Digital twin, Civilian evacuation, Artificial intelligence, Data mapping, Digital technology, Technology assessment, Data integration
Abstract: Buildings face threats from various emergencies, with emergency evacuation being a key measure for occupant safety. However, enhancing evacuation efficiency necessitates detailed studies of building characteristics and human behaviors. Despite this, a systematic review of digital twin technologies for emergency evacuation is still lacking. Therefore, by collecting and analyzing literature from 2004 to 2025 using PRISMA methodology, this study first proposes a conceptual digital twin framework that integrates buildings, occupants, and their interactions, encompassing the entire loop of sensing, updating, simulation, and decision-making. The current research has made significant progresses in areas such as basic virtual modeling, one-way data mapping, and preliminary bidirectional interaction. However, studies and applications of digital twins remain in the developmental stage, with most at maturity levels L0-L2, while L4-L5 applications are still relatively scarce. It is suggested that the future development of digital twin-based evacuation systems must rely on multidisciplinary collaboration to achieve breakthroughs, including optimizing underlying mechanisms to enhance data and system integration; improving sensing accuracy and developing adaptive algorithms for simulation, prediction and assessment; integrating emerging artificial intelligence technologies while addressing data ethics; and enhancing computational efficiency to strengthen system robustness. [ABSTRACT FROM AUTHOR]
Copyright of Advanced Engineering Informatics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 185746184
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Digital twin of buildings and occupants for emergency evacuation: Framework, technologies, applications and trends.
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  Data: <searchLink fieldCode="AR" term="%22Lin%2C+Jia-Rui%22">Lin, Jia-Rui</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> lin611@tsinghua.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Chen%2C+Ke-Yin%22">Chen, Ke-Yin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> chenky22@mails.tsinghua.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Song%2C+Sheng-Yu%22">Song, Sheng-Yu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cai%2C+Yun-Hong%22">Cai, Yun-Hong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pan%2C+Peng%22">Pan, Peng</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> panpeng@tsinghua.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Deng%2C+Yi-Chuan%22">Deng, Yi-Chuan</searchLink><relatesTo>3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Advanced+Engineering+Informatics%22">Advanced Engineering Informatics</searchLink>. Jul2025, Vol. 66, pN.PAG-N.PAG. 1p.
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  Data: <searchLink fieldCode="DE" term="%22Digital+twin%22">Digital twin</searchLink><br /><searchLink fieldCode="DE" term="%22Civilian+evacuation%22">Civilian evacuation</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Data+mapping%22">Data mapping</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+technology%22">Digital technology</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+assessment%22">Technology assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Data+integration%22">Data integration</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Buildings face threats from various emergencies, with emergency evacuation being a key measure for occupant safety. However, enhancing evacuation efficiency necessitates detailed studies of building characteristics and human behaviors. Despite this, a systematic review of digital twin technologies for emergency evacuation is still lacking. Therefore, by collecting and analyzing literature from 2004 to 2025 using PRISMA methodology, this study first proposes a conceptual digital twin framework that integrates buildings, occupants, and their interactions, encompassing the entire loop of sensing, updating, simulation, and decision-making. The current research has made significant progresses in areas such as basic virtual modeling, one-way data mapping, and preliminary bidirectional interaction. However, studies and applications of digital twins remain in the developmental stage, with most at maturity levels L0-L2, while L4-L5 applications are still relatively scarce. It is suggested that the future development of digital twin-based evacuation systems must rely on multidisciplinary collaboration to achieve breakthroughs, including optimizing underlying mechanisms to enhance data and system integration; improving sensing accuracy and developing adaptive algorithms for simulation, prediction and assessment; integrating emerging artificial intelligence technologies while addressing data ethics; and enhancing computational efficiency to strengthen system robustness. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Advanced Engineering Informatics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=185746184
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.aei.2025.103419
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      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Digital twin
        Type: general
      – SubjectFull: Civilian evacuation
        Type: general
      – SubjectFull: Artificial intelligence
        Type: general
      – SubjectFull: Data mapping
        Type: general
      – SubjectFull: Digital technology
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      – SubjectFull: Technology assessment
        Type: general
      – SubjectFull: Data integration
        Type: general
    Titles:
      – TitleFull: Digital twin of buildings and occupants for emergency evacuation: Framework, technologies, applications and trends.
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            NameFull: Lin, Jia-Rui
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            NameFull: Chen, Ke-Yin
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            NameFull: Song, Sheng-Yu
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            NameFull: Cai, Yun-Hong
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            NameFull: Pan, Peng
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            – D: 01
              M: 07
              Text: Jul2025
              Type: published
              Y: 2025
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              Value: 66
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