Digital twin technology supporting urban public space renewal.
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| Title: | Digital twin technology supporting urban public space renewal. |
|---|---|
| Authors: | Li, Xintong1 xintong@hotmail.com, Tang, Yixuan2 tangyixuan_tyx@outlook.com, Zhao, Yiyuan1 Yiyuan_Zhao16@outlook.com |
| Source: | Archives of Civil Engineering (Polish Academy of Sciences). 2026, Vol. 72 Issue 1, p241-253. 13p. |
| Subjects: | Digital twin, Public spaces, Genetic algorithms, Participation, Box-Jenkins forecasting, Urban renewal, Resource allocation, Prediction models |
| Abstract: | Urban public space, as a core component of the urban, is an important carrier for the residents' quality of life, social interaction and cultural inheritance. With the deepening of urbanization, urban public space is facing unprecedented challenges, including aging space, single function, environmental degradation, and mismatch with residents' needs, etc. This paper comprehensively discusses the application of digital twin technology in urban public space renewal, and systematically analyzes its core role in enhancing the function of public space, promoting the optimization of resource allocation, and reinforcing the ability of predictive analysis from the theoretical framework to specific countermeasures. Through the introduction of genetic algorithm and ARIMA model, the technical support of complex resource allocation and future trend prediction is shown; and the successful application and significant effect of digital twin technology in actual projects are demonstrated with the examples of The Bund in Shanghai and Marina Bay Gardens in Singapore. In addition, a detailed assessment of data security, technical compatibility, public participation and cost-effectiveness is made, and targeted countermeasures and recommendations are proposed. [ABSTRACT FROM AUTHOR] |
| Copyright of Archives of Civil Engineering (Polish Academy of Sciences) is the property of Polish Academy of Sciences 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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| Items | – Name: Title Label: Title Group: Ti Data: Digital twin technology supporting urban public space renewal. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Li%2C+Xintong%22">Li, Xintong</searchLink><relatesTo>1</relatesTo><i> xintong@hotmail.com</i><br /><searchLink fieldCode="AR" term="%22Tang%2C+Yixuan%22">Tang, Yixuan</searchLink><relatesTo>2</relatesTo><i> tangyixuan_tyx@outlook.com</i><br /><searchLink fieldCode="AR" term="%22Zhao%2C+Yiyuan%22">Zhao, Yiyuan</searchLink><relatesTo>1</relatesTo><i> Yiyuan_Zhao16@outlook.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Archives+of+Civil+Engineering+%28Polish+Academy+of+Sciences%29%22">Archives of Civil Engineering (Polish Academy of Sciences)</searchLink>. 2026, Vol. 72 Issue 1, p241-253. 13p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Digital+twin%22">Digital twin</searchLink><br /><searchLink fieldCode="DE" term="%22Public+spaces%22">Public spaces</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Participation%22">Participation</searchLink><br /><searchLink fieldCode="DE" term="%22Box-Jenkins+forecasting%22">Box-Jenkins forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Urban+renewal%22">Urban renewal</searchLink><br /><searchLink fieldCode="DE" term="%22Resource+allocation%22">Resource allocation</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Urban public space, as a core component of the urban, is an important carrier for the residents' quality of life, social interaction and cultural inheritance. With the deepening of urbanization, urban public space is facing unprecedented challenges, including aging space, single function, environmental degradation, and mismatch with residents' needs, etc. This paper comprehensively discusses the application of digital twin technology in urban public space renewal, and systematically analyzes its core role in enhancing the function of public space, promoting the optimization of resource allocation, and reinforcing the ability of predictive analysis from the theoretical framework to specific countermeasures. Through the introduction of genetic algorithm and ARIMA model, the technical support of complex resource allocation and future trend prediction is shown; and the successful application and significant effect of digital twin technology in actual projects are demonstrated with the examples of The Bund in Shanghai and Marina Bay Gardens in Singapore. In addition, a detailed assessment of data security, technical compatibility, public participation and cost-effectiveness is made, and targeted countermeasures and recommendations are proposed. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Archives of Civil Engineering (Polish Academy of Sciences) is the property of Polish Academy of Sciences 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.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.24425/ace.2026.157471 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 13 StartPage: 241 Subjects: – SubjectFull: Digital twin Type: general – SubjectFull: Public spaces Type: general – SubjectFull: Genetic algorithms Type: general – SubjectFull: Participation Type: general – SubjectFull: Box-Jenkins forecasting Type: general – SubjectFull: Urban renewal Type: general – SubjectFull: Resource allocation Type: general – SubjectFull: Prediction models Type: general Titles: – TitleFull: Digital twin technology supporting urban public space renewal. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Li, Xintong – PersonEntity: Name: NameFull: Tang, Yixuan – PersonEntity: Name: NameFull: Zhao, Yiyuan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 12302945 Numbering: – Type: volume Value: 72 – Type: issue Value: 1 Titles: – TitleFull: Archives of Civil Engineering (Polish Academy of Sciences) Type: main |
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