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Achieving Smart Water Network Management Through Semantically Driven Cognitive Systems

Abstract : 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.
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Thomas Beach, Shaun Howell, Julia Terlet, Wanqing Zhao, Yacine Rezgui. Achieving Smart Water Network Management Through Semantically Driven Cognitive Systems. 19th Working Conference on Virtual Enterprises (PRO-VE), Sep 2018, Cardiff, United Kingdom. pp.478-485, ⟨10.1007/978-3-319-99127-6_41⟩. ⟨hal-02191190⟩

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