Semantic 3D city interfaces—Intelligent interactions on dynamic geospatial knowledge graphs

IF 2.4 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE DataCentric Engineering Pub Date : 2023-09-06 DOI:10.1017/dce.2023.14
A. Chadzynski, Shiying Li, Ayda Grisiute, Jefferson Chua, Markus Hofmeister, Jingya Yan, Huay Yi Tai, Emily Lloyd, Yi Kai Tsai, Mehal Agarwal, J. Akroyd, P. Herthogs, Markus Kraft
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引用次数: 2

Abstract

Abstract This article presents a system architecture and a set of interfaces that can build scalable information systems capable of large city modeling based on dynamic geospatial knowledge graphs to avoid pitfalls of Web 2.0 applications while blending artificial and human intelligence during the knowledge enhancement processes. We designed and developed a GeoSpatial Processor, an SQL2SPARQL Transformer, and a geospatial tiles ordering tasks and integrated them into a City Export Agent to visualize and interact with city models on an augmented 3D web client. We designed a Thematic Surface Discovery Agent to automatically upgrade the model’s level of detail to interact with thematic parts of city objects by other agents. We developed a City Information Agent to help retrieve contextual information, provide data concerning city regulations, and work with a City Energy Analyst Agent that automatically estimates the energy demands for city model members. We designed a Distance Agent to track the interactions with the model members on the web, calculate distances between objects of interest, and add new knowledge to the Cities Knowledge Graph. The logical foundations and CityGML-based conceptual schema used to describe cities in terms of the OntoCityGML ontology, together with the system of intelligent autonomous agents based on the J-Park Simulator Agent Framework, make such systems capable of assessing and maintaining ground truths with certainty. This new era of GeoWeb 2.5 systems lowers the risk of deliberate misinformation within geography web systems used for modeling critical infrastructures.
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语义三维城市界面——动态地理空间知识图谱上的智能交互
摘要本文提出了一种系统架构和一组接口,可以基于动态地理空间知识图构建能够进行大城市建模的可扩展信息系统,以避免Web2.0应用程序的陷阱,同时在知识增强过程中融合人工智能和人工智能。我们设计并开发了GeoSpatial处理器、SQL2SPARQL转换器和地理空间瓦片排序任务,并将它们集成到城市导出代理中,以便在增强的3D web客户端上可视化城市模型并与之交互。我们设计了一个主题表面发现代理,以自动升级模型的细节级别,从而通过其他代理与城市对象的主题部分进行交互。我们开发了一个城市信息代理,以帮助检索上下文信息,提供有关城市法规的数据,并与城市能源分析代理合作,自动估计城市模型成员的能源需求。我们设计了一个距离代理来跟踪与网络上模型成员的交互,计算感兴趣对象之间的距离,并将新知识添加到城市知识图中。基于OntoCityGML本体描述城市的逻辑基础和基于CityGML的概念模式,以及基于J-Park模拟器Agent框架的智能自治Agent系统,使这些系统能够确定地评估和维护地面实况。GeoWeb 2.5系统的这一新时代降低了用于建模关键基础设施的地理web系统中故意错误信息的风险。
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来源期刊
DataCentric Engineering
DataCentric Engineering Engineering-General Engineering
CiteScore
5.60
自引率
0.00%
发文量
26
审稿时长
12 weeks
期刊最新文献
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