Knowledge Discovery in 3D Geospatial Spaces: Towards an Integrated BIM, 3D GIS and IoT Data Framework

3D 地理空间空间中的知识发现：迈向集成 BIM、3D GIS 和 IoT 数据框架

• 批准号: RGPIN-2017-05659
• 负责人: JadidiMardkheh, Amaneh(Mojgan)
• 金额: $ 1.46万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=711759
• 关键词: Knowledge; Discovery; 3D; Geospatial; Spaces

The world is entering the period of smart cities. The Internet of Things (IoT) and information-technology infrastructure are fundamental to smart cities, a network of connected smart devices, sensors, and big-data analytics. By 2020, estimates are that there will be 80 billion connected devices worldwide and over 5 billion Internet users. Connectivity is inevitable and will include all facets of our lives, seamlessly bringing together work, home and surrounding environments. In this context, 3D virtual city space is key to helping smart cities manage and monitor indoor-outdoor dynamics. Canadian cities are determined to achieve the goal of becoming smart cities. To foster dynamic city applications such as business growth and solutions for monitoring infrastructure, Toronto and Montreal have both launched 3D open data to the public. However, further research is required to deal with multi-scale analysis and visualization in a virtual space, extended from city-scale to building structures and vice-versa seamlessly through the temporal scale. The main goal of this research is to increase our knowledge of how a variety of data coming from Building Information Model (BIM), 3D Geographical Information Systems (GIS) and IoT, integrate into a single environment to conduct spatiotemporal analytics. Our research will advance knowledge by identifying ontology, semantics and the geometry definition of integrated data through a multidimensional graph-structure. Nine HQP will be trained by working on the development of 1) A comprehensive, integrated data modeling framework handling BIM, GIS and IoT stream data; 2) An analytical approach for data mining in 3D indoor-outdoor virtual model in order to discover knowledge; 3) Spatial aggregation operations for multi-scale representation of discovered knowledge in a seamless indoor-outdoor virtual model; 4) A geospatial data sharing, interoperability and quality assessment framework for the integration of BIM, GIS and IoT. Knowledge gained from our research will enable new technologies that have an aggregated and granulated image of massive amounts of 3D indoor-outdoor data through a virtual space connected with IoT stream information. This knowledge will have a significant impact on the Canadian geospatial industry sectors. Our research will also provide technological advancement, innovative approaches and deep insight into the standardization of 3D data sharing. The results will be applied to a wide range of smart cities applications such as energy efficiency, emergency management, infrastructure monitoring, and facility management.

世界正在进入智慧城市时期。物联网（IoT）和信息技术基础架构是智能城市的基础，这是一个连接的智能设备，传感器和大数据分析网络。到2020年，估计全球将有800亿个连接的设备和超过50亿个互联网用户。连通性是不可避免的，将包括我们生活的所有方面，无缝地将工作，家庭和周围环境融合在一起。在这种情况下，3D虚拟城市空间是帮助智能城市管理和监视室内室外动态的关键。加拿大城市决心实现成为智慧城市的目标。为了促进动态城市应用，例如业务增长和监测基础设施的解决方案，多伦多和蒙特利尔都向公众启动了3D开放数据。但是，需要进一步的研究来处理虚拟空间中的多尺度分析和可视化，从城市规模扩展到建筑结构，并通过时间尺度无缝地无缝。 这项研究的主要目的是增加我们对来自建筑信息模型（BIM），3D地理信息系统（GIS）和IoT的各种数据的了解，并将其集成到单个环境中以进行时空分析。我们的研究将通过多维图结构来识别集成数据的本体论，语义和几何定义来提高知识。九个HQP将通过开发1）培训1）一个全面的，集成的数据建模框架处理BIM，GIS和IOT流数据； 2）在3D室内外虚拟模型中用于数据挖掘的分析方法，以发现知识； 3）在无缝室内室外虚拟模型中发现知识的多尺度表示的空间聚合操作； 4）用于集成BIM，GIS和IoT的地理空间数据共享，互操作性和质量评估框架。 从我们的研究中获得的知识将使新技术通过与IoT流信息相关的虚拟空间，具有大量3D室内室外数据的汇总和磨合图像。这些知识将对加拿大地理空间行业产生重大影响。我们的研究还将提供技术进步，创新的方法，并深入了解3D数据共享的标准化。结果将应用于各种智能城市应用程序，例如能源效率，应急管理，基础设施监控和设施管理。