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    <identifier>10.57760/sciencedb.33155</identifier>
    <datestamp>2025-12-12T21:58:35Z</datestamp>
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  <dc:date>2025-12-12</dc:date>
  <dc:title>Digital Twin Campus System Driven by Multi-modal AIoT</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.33155</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>	To address issues such as reliance on manual experience, static planning, data latency, inefficient decision-making, and the inability to support multimodal decision-making in traditional resource allocation models, this paper develops digital twin technology and artificial intelligence models. Using a university in Nanning as a research prototype, a three-dimensional model was constructed to create a dynamic virtual mirror of the physical entity. By integrating real-time data from the Internet of Things (IoT) and sensors, the system enables full lifecycle simulation, intelligent prediction, and parameter optimization, significantly enhancing the intuitiveness of decision-making and the efficiency of management in smart campuses.&amp;nbsp;</dc:description>
  <dc:subject>multimodal model; 3D visualization technology; smart campus; virtual reality technology</dc:subject>
  <dc:creator>Fan Zihao</dc:creator>
  <dc:creator>Zhou Min</dc:creator>
  <dc:creator>Zhu Xiaolei</dc:creator>
  <dc:creator>Shi Wenyan</dc:creator>
  <dc:creator>He Gang</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
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  <dc:publisher>Science Data Bank</dc:publisher>
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