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Achieving Smart Water Network Management Through Semantically Driven Cognitive Systems

机译:通过语义驱动的认知系统实现智能水网络管理

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Achieving necessary resilience levels in urban water networks is a challenging proposition, with water network operators required to ensure a constant supply of treated water at pre-set pressure levels to a huge number of homes and businesses, all within strict budgetary restrictions. To achieve this, water network operators are required to overcome significant obstacles, including ageing assets within their infrastructure, the wide geographical area over which assets are spread, problematic internet connectivity in remote locations and a lack of interoperability between water network operator ICT systems. These issues act as key blockers for the deployment of smart water network management technologies such as optimisation, data driven modelling and dynamic water demand management. This paper presents how the use of a set cognitive analytic smart water components, underpinned by semantic modelling of the water network, can overcome these obstacles. The architecture and underpinning semantics of cognitive components are described along with how communication between these components is achieved. Two case studies are presented to demonstrate how the deployment of smart technologies can improve water network efficiency.
机译:在城市供水网络中实现必要的恢复力水平是一项具有挑战性的提议,因为供水网络运营商必须确保在预设的压力水平下向大量家庭和企业稳定供应经过处理的水,且均在严格的预算限制内。为此,水网运营商需要克服重大障碍,包括其基础设施中的资产老化,资产分布的广阔地理区域,偏远地区的互联网连接出现问题以及水网运营商ICT系统之间缺乏互操作性。这些问题成为智能水网络管理技术(例如优化,数据驱动的建模和动态水需求管理)的部署的主要障碍。本文介绍了在水网络语义建模的基础上使用一组认知分析智能水组件如何克服这些障碍。描述了认知组件的体系结构和基础语义,以及如何实现这些组件之间的通信。提出了两个案例研究,以展示智能技术的部署如何提高水网络的效率。

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