Intelligent Urban Water Infrastructure Management

被引:0
|
作者
Savic, Dragan A. [1 ]
Bicik, Josef [1 ]
Morley, Mark S. [1 ]
Duncan, Andrew [1 ]
Kapelan, Zoran [1 ]
Djordjevic, Slobodan [1 ]
Keedwell, Edward C. [1 ]
机构
[1] Univ Exeter, Ctr Water Syst, Exeter EX4 4QJ, Devon, England
基金
英国工程与自然科学研究理事会;
关键词
urban water; infrastructure; intelligent/smart systems; decision support; real-time; sensor; ARTIFICIAL NEURAL-NETWORK;
D O I
暂无
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Urban population growth together with other pressures, such as climate change, create enormous challenges to provision of urban infrastructure services, including gas, electricity, transport, water, etc. Smart-grid technology is viewed as the way forward to ensure that infrastructure networks are flexible, accessible, reliable and economical. "Intelligent water networks" take advantage of the latest information and communication technologies to gather and act on information to minimise waste and deliver more sustainable water services. The effective management of water distribution, urban drainage and sewerage infrastructure is likely to require increasingly sophisticated computational techniques to keep pace with the level of data that is collected from measurement instruments in the field. This paper describes two examples of intelligent systems developed to utilise this increasingly available real-time sensed information in the urban water environment. The first deals with the failure-management decision-support system for water distribution networks, NEPTUNE, that takes advantage of intelligent computational methods and tools applied to near real-time logger data providing pressures, flows and tank levels at selected points throughout the system. The second, called RAPIDS, deals with urban drainage systems and the utilisation of rainfall data to predict flooding of urban areas in near real-time. The two systems have the potential to provide early warning and scenario testing for decision makers within reasonable time, this being a key requirement of such systems. Computational methods that require hours or days to run will not be able to keep pace with fast-changing situations such as pipe bursts or manhole flooding and thus the systems developed are able to react in close to real time.
引用
收藏
页码:319 / 336
页数:18
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