Arab historic centers face a lack of collaborative digital models that restore the “spirit of the place” and go beyond physical documentation. This study builds on this research gap to propose a digital framework that integrates the metaverse and artificial intelligence to revitalize the historic center of Najaf (the neighborhoods of Al-Buraq, Al-Mashraq, Al-Huwaish, and Al-Amara). The goal of the study is to build a replicable model that supports sustainable preservation and engages the local community in decision-making.The research relied on 3D modeling of the urban fabric using GIS and Photogrammetry/LiDAR, then integrated the model into metaverse platforms to conduct immersive experiences. Behavioral data were collected within the platform and questionnaire responses from a purposive sample (n = 60). Statistical analysis was conducted (descriptive statistics, t-test, ANOVA, Pearson’s correlation) while ensuring internal consistency (Cronbach’s alpha = 0.89) and spatial consistency (>90%).The results showed increased perception of “spirit of place” (mean = 4.50/5), immersion (4.34/5), and the effectiveness of artificial intelligence (4.30/5), with over 80% confirming a stronger sense of place identity compared to traditional media. A strong correlation was found between immersion and perception of spirit of place (r = 0.78, p < 0.01), with significant age differences in favor of those under 25 years old. Hotspots of interest were also identified around the alleys leading to the shrine and traditional markets.The study presents an operational framework that moves preservation from documentation to interactive revitalization by combining sensory immersion, algorithmic analysis, and community engagement. This framework is generalizable and aligned with Sustainable Development Goal 11.4, enabling decision-makers to test improvement scenarios in a safe environment prior to field intervention.

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Reviving the Spirit of Place in Historic Centers Through a Participatory Digital Framework: Employing Metaverse and Artificial Intelligence Technologies for Sustainable Conservation in the Najaf Center

  • Sabeeh Lafta Farhan,
  • Raghad Mahdi Alameedy

摘要

Arab historic centers face a lack of collaborative digital models that restore the “spirit of the place” and go beyond physical documentation. This study builds on this research gap to propose a digital framework that integrates the metaverse and artificial intelligence to revitalize the historic center of Najaf (the neighborhoods of Al-Buraq, Al-Mashraq, Al-Huwaish, and Al-Amara). The goal of the study is to build a replicable model that supports sustainable preservation and engages the local community in decision-making.The research relied on 3D modeling of the urban fabric using GIS and Photogrammetry/LiDAR, then integrated the model into metaverse platforms to conduct immersive experiences. Behavioral data were collected within the platform and questionnaire responses from a purposive sample (n = 60). Statistical analysis was conducted (descriptive statistics, t-test, ANOVA, Pearson’s correlation) while ensuring internal consistency (Cronbach’s alpha = 0.89) and spatial consistency (>90%).The results showed increased perception of “spirit of place” (mean = 4.50/5), immersion (4.34/5), and the effectiveness of artificial intelligence (4.30/5), with over 80% confirming a stronger sense of place identity compared to traditional media. A strong correlation was found between immersion and perception of spirit of place (r = 0.78, p < 0.01), with significant age differences in favor of those under 25 years old. Hotspots of interest were also identified around the alleys leading to the shrine and traditional markets.The study presents an operational framework that moves preservation from documentation to interactive revitalization by combining sensory immersion, algorithmic analysis, and community engagement. This framework is generalizable and aligned with Sustainable Development Goal 11.4, enabling decision-makers to test improvement scenarios in a safe environment prior to field intervention.