A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Building energy performance assessment using linked data and cross-domain semantic reasoning
Abstract Cross-domain information is essential for building energy performance assessment. The heterogeneous nature of this information is a major source for inefficient assessments. The semantic web provides a flexible pathway for addressing recognised interoperability issues. However, further implicit knowledge in cross-domain information could provide meaningful solutions for such assessments. This paper aims to develop a conceptual framework that links cross-domain information, infers implicit knowledge, and empowers building managers with insightful assessments. The framework integrates Web Ontology Language (OWL) ontologies, Resource Description Framework (RDF) instances, and a set of predefined rules to infer implicit knowledge, which can satisfy data requirements of performance metrics and enable meaningful performance assessments. Then building managers can identify inefficient building operations and improve energy efficiency while maintaining desired building functions. This approach reduces burdensome intervention from the managers when compared with traditional solutions. A demonstration highlights the engineering value by evaluating energy performance of a university building.
Highlights The work links cross-domain information for building energy performance assessment. Semantic reasoning is employed for inferring implicit knowledge in this information Inference rules are defined to satisfy data requirements of key performance metrics. Results indicate the work provides comprehensive assessments for building managers.
Building energy performance assessment using linked data and cross-domain semantic reasoning
Abstract Cross-domain information is essential for building energy performance assessment. The heterogeneous nature of this information is a major source for inefficient assessments. The semantic web provides a flexible pathway for addressing recognised interoperability issues. However, further implicit knowledge in cross-domain information could provide meaningful solutions for such assessments. This paper aims to develop a conceptual framework that links cross-domain information, infers implicit knowledge, and empowers building managers with insightful assessments. The framework integrates Web Ontology Language (OWL) ontologies, Resource Description Framework (RDF) instances, and a set of predefined rules to infer implicit knowledge, which can satisfy data requirements of performance metrics and enable meaningful performance assessments. Then building managers can identify inefficient building operations and improve energy efficiency while maintaining desired building functions. This approach reduces burdensome intervention from the managers when compared with traditional solutions. A demonstration highlights the engineering value by evaluating energy performance of a university building.
Highlights The work links cross-domain information for building energy performance assessment. Semantic reasoning is employed for inferring implicit knowledge in this information Inference rules are defined to satisfy data requirements of key performance metrics. Results indicate the work provides comprehensive assessments for building managers.
Building energy performance assessment using linked data and cross-domain semantic reasoning
Hu, Shushan (author) / Wang, Jiale (author) / Hoare, Cathal (author) / Li, Yehong (author) / Pauwels, Pieter (author) / O'Donnell, James (author)
2021-01-18
Article (Journal)
Electronic Resource
English
| British Library Online Contents | 2013