Integrating building and urban semantics to empower smart water solutions

Howell, Shaun, Rezgui, Yacine ORCID: https://orcid.org/0000-0002-5711-8400 and Beach, Thomas ORCID: https://orcid.org/0000-0001-5610-8027 2017. Integrating building and urban semantics to empower smart water solutions. Automation in Construction 81 , pp. 434-448. 10.1016/j.autcon.2017.02.004

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Abstract

Current urban water research involves intelligent sensing, systems integration, proactive users and data-driven management through advanced analytics. The convergence of building information modeling with the smart water field provides an opportunity to transcend existing operational barriers. Such research would pave the way for demand-side management, active consumers, and demand-optimized networks, through interoperability and a system of systems approach. This paper presents a semantic knowledge management service and domain ontology which support a novel cloud-edge solution, by unifying domestic socio-technical water systems with clean and waste networks at an urban scale, to deliver value-added services for consumers and network operators. The web service integrates state of the art sensing, data analytics and middleware components. We propose an ontology for the domain which describes smart homes, smart metering, telemetry, and geographic information systems, alongside social concepts. This integrates previously isolated systems as well as supply and demand-side interventions, to improve system performance. A use case of demand-optimized management is introduced, and smart home application interoperability is demonstrated, before the performance of the semantic web service is presented and compared to alternatives. Our findings suggest that semantic web technologies and IoT can merge to bring together large data models with dynamic data streams, to support powerful applications in the operational phase of built environment systems.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Uncontrolled Keywords:	Water management; BIM; Demand-optimized management; Interoperability; Intelligent sensing; Big data; Data analytics; Ontology; Semantic web; Internet of Things
Publisher:	Elsevier
ISSN:	0926-5805
Funders:	European Commission, Engineering and Physical Sciences Research Council
Date of First Compliant Deposit:	6 April 2017
Date of Acceptance:	26 February 2017
Last Modified:	07 May 2023 20:43
URI:	https://orca.cardiff.ac.uk/id/eprint/99364

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