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Beach, Thomas, Howell, Shaun, Terlet, Julia, Zhao, Wanqing 
ORCID: https://orcid.org/0000-0001-6160-9547 and Rezgui, Yacine
(2018)
Achieving Smart Water Network Management Through Semantically Driven Cognitive Systems.
In:
IFIP Advances in Information and Communication Technology.
Collaborative Networks of Cognitive Systems
.
UNSPECIFIED, pp. 478-485.
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.
| Item Type: | Book Section |
|---|---|
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Smart Emerging Technologies |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 03 Jul 2020 23:32 |
| Last Modified: | 18 Aug 2023 01:00 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/75893 |
| DOI: | 10.1007/978-3-319-99127-6_41 |
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