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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">JERA</journal-id><journal-title-group><journal-title>Journal of Electronic Research and Application</journal-title></journal-title-group><issn>2208-3502</issn><eissn>2208-3510</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/jera.v9i6.13172</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Digital Twin Spatiotemporal Indexing Engine: “Edge Cloud” Layered Storage and Fast Backtracking of Real-Time Streaming Data</title><url>https://artdesignp.com/journal/JERA/9/6/10.26689/jera.v9i6.13172</url><author>HuangHuanjing</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>9</volume><issue>6</issue><history><date date-type="pub"><published-time>2025-12-16</published-time></date></history><abstract>This article examines the design and implementation of a digital twin spatiotemporal indexing engine. It outlines the core theoretical foundations, including spatiotemporal mapping mechanisms, and discusses key enabling technologies such as hybrid spatiotemporal indexing structures, edge-cloud collaborative storage architectures, and protocol conversion middleware. The study further evaluates system performance through an experimental platform, comparing a layered storage architecture with traditional storage models. The results demonstrate clear advantages in terms of efficiency, scalability, and responsiveness. Finally, the paper explores practical application scenarios and outlines future development directions for next-generation spatiotemporal indexing engines in digital twin systems.</abstract><keywords/></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>Friederich J, Francis D, Lazarova-Molnar S, et al., 2022, A Framework for Data-Driven Digital Twins of Smart Manufacturing Systems. 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