CPS: Synergy: Collaborative Research: Mapping and Querying Underground Infrastructure Systems

实现智慧城市愿景的挑战之一是改善地下基础设施的状况。例如，美国的大城市有数千英里老化的水管，导致每年数百次断裂，很大一部分水的消耗是无法计算的。该项目的目标是开发模型和方法，以生成、分析和共享地下基础设施系统（如水、气、电和下水道网络）的数据。来自伊利诺伊大学芝加哥分校、布朗大学和西北大学的跨学科研究小组将利用与芝加哥市和伊利诺伊州埃文斯顿市的合作伙伴关系，使方法和发现与他们的利益相关者相关。研究成果将纳入三所院校的课程。拓展工作包括为K-12学生举办活动，从数据和计算的角度培养对地下基础设施的认识。该项目的成果最终将帮助市政当局以更有效的方式维护和翻新民用基础设施。城市是一个大规模的网络物理系统，对其基础设施的精确了解对于为未来的智慧城市奠定基础至关重要。该方案采用以信息为中心的方法，基于主题数据层之间的复杂交互，从不完整和不精确的数据出发，开发、可视化、查询、分析并提供对城市地下基础设施的全面表示的访问。具体而言，该项目有以下主要技术组成部分：(1)从纸质地图、CAD图纸和其他遗留数据源生成基于gis的地下基础设施系统精确表示；(2)结合原理概述图和详细几何表示的多层网络可视化；(3)地下基础设施系统时空与网络数据融合的查询处理算法；(4)跨越异构地理空间数据源并纳入不确定性和约束的数据分析；(5)在需要知道的基础上选择性地接触利益相关者，促进数据共享；(6)与芝加哥和埃文斯顿市合作进行评估。

One of the challenges toward achieving the vision of smart cities is improving the state of the underground infrastructure. For example, large US cities have thousands of miles of aging water mains, resulting in hundreds of breaks every year, and a large percentage of water consumption that is unaccounted for. The goal of this project is to develop models and methods to generate, analyze, and share data on underground infrastructure systems, such as water, gas, electricity , and sewer networks. The interdisciplinary team of investigators from the University of Illinois at Chicago, Brown University, and Northwestern University will leverage partnerships with the cities of Chicago and Evanston, Illinois, to make the approach and findings relevant to their stakeholders. Research results will be incorporated in courses at the three institutions. Outreach efforts include events for K-12 students to develop awareness about underground infrastructure from a data and computational perspective. The results of the project will ultimately help municipalities maintain and renovate civil infrastructure in a more effective manner.Cities are cyber-physical systems on a grand scale, and developing a precise knowledge of their infrastructure is critical to building a foundation for the future smart city. This proposal takes an information centric approach based on the complex interaction among thematic data layers to developing, visualizing, querying, analyzing, and providing access to a comprehensive representation of the urban underground infrastructure starting from incomplete and imprecise data. Specifically, the project has the following main technical components: (1) Generation of accurate GIS-based representations of underground infrastructure systems from paper maps, CAD drawings, and other legacy data sources; (2) Visualization of multi-layer networks combining schematic overview diagrams with detailed geometric representations; (3) Query processing algorithms for integrating spatial, temporal, and network data about underground infrastructure systems; (4) Data analytics spanning heterogeneous geospatial data sources and incorporating uncertainty and constraints; (5) Selective access to stakeholders on a need-to-know basis and facilitating data sharing; and (6) Evaluation in collaboration with the cities of Chicago and Evanston.