This paper outlines and discusses a few associated details of a smart cities approach to the mapping and condition assessment of urban underground infrastructure. Underground utilities are critical infrastructure for all modern cities. They carry drinking water, storm water, sewage, natural gas, electric power, telecommunications, steam, etc. In most cities, the underground infrastructure reflects the growth and history of the city. Many components are aging, in unknown locations with congested configurations, and in unknown condition. The technique uses sensing and information technology to determine the state of infrastructure and provide it in an appropriate, timely and secure format for managers, planners and users. The sensors include ground penetrating radar and buried sensors for persistent sensing of localized conditions. Signal processing and pattern recognition techniques convert the data in information-laden databases for use in analytics, graphical presentations, metering and planning. The presented data are from construction of the St. Paul St. CCTA Bus Station Project in Burlington, VT; utility replacement sites in Winooski, VT; and laboratory tests of smart phone position registration and magnetic signaling. The soil conditions encountered are favorable for GPR sensing and make it possible to locate buried pipes and soil layers. The present state of the art is that the data collection and processing procedures are manual and somewhat tedious, but that solutions for automating these procedures appear to be viable. Magnetic signaling with moving permanent magnets has the potential for sending lowfrequency telemetry signals through soils that are largely impenetrable by other electromagnetic waves.
Dryver Huston, Tian Xia, Yu Zhang, Taian Fan, Dan Orfeo, and Jonathan Razinger, "Urban underground infrastructure mapping and assessment," Proc. SPIE 10168, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2017, 101680M (Presented at SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring: March 27, 2017; Published: 12 April 2017); https://doi.org/10.1117/12.2263530.
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