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，美国大城市有数千英里长的老化自来水管道，导致每年数百次破裂，有很大一部分用水量下落不明。该项目的目标是开发模型和方法来生成、分析和共享有关地下基础设施系统的数据，例如水、天然气、电力和下水道网络。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调查团队将利用与芝加哥和伊利诺伊州埃文斯顿这两个城市的合作伙伴关系，使方法和调查结果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。外展工作包括为K-12学生举办活动，从数据和计算的角度提高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改造民用基础设施。城市是大规模的网络物理系统，发展对其基础设施的准确了解对于为未来的智能城市奠定基础至关重要。该建议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，从不完整和不准确的数据开始，开发、可视化、查询、分析和提供对城市地下基础设施的全面表示。具体地说，该项目有以下主要技术组成部分：(1)从纸质地图、CAD绘图和其他遗留数据源生成基于地理信息系统的准确地下基础设施系统表示；(2)结合示意图概述图和详细几何表示的多层网络的可视化；(3)用于集成关于地下基础设施系统的空间、时间和网络数据的查询处理算法；(4)跨越不同地理空间数据源的数据分析，并纳入不确定性和约束；(5)根据需要了解的选择性访问利益攸关方并促进数据共享；以及(6)与芝加哥和埃文斯顿两市合作进行评估。

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.