A decision support system for urban infrastructure inter-asset management employing domain ontologies and qualitative uncertainty-based reasoning
Urban infrastructure assets (e.g. roads, water pipes) perform critical functions to the health and well-being of society. Although it has been widely recognised that different infrastructure assets are highly interconnected, infrastructure management in practice such as planning, installation and ma...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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2020
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| Online Access: | https://eprints.nottingham.ac.uk/60823/ |
| _version_ | 1848799810312732672 |
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| author | Wei, Lijun Du, Heshan Mahesar, Quratul-ain Al Ammari, Kareem Magee, Derek R. Clarke, Barry Dimitrova, Vania Gunn, David Entwisle, David Reeves, Helen Cohn, Anthony G. |
| author_facet | Wei, Lijun Du, Heshan Mahesar, Quratul-ain Al Ammari, Kareem Magee, Derek R. Clarke, Barry Dimitrova, Vania Gunn, David Entwisle, David Reeves, Helen Cohn, Anthony G. |
| author_sort | Wei, Lijun |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Urban infrastructure assets (e.g. roads, water pipes) perform critical functions to the health and well-being of society. Although it has been widely recognised that different infrastructure assets are highly interconnected, infrastructure management in practice such as planning, installation and maintenance are often undertaken by different stakeholders without considering these dependencies due to the lack of relevant data and cross-domain knowledge, which may cause unexpected cascading social, economic and environmental effects. In this paper, we present a knowledge based decision support system for urban infrastructure inter-asset management. By considering various infrastructure assets (e.g. road, ground, cable), triggers (e.g. pipe leaking) and potential consequences (e.g. tra c disruption) as a holistic system, we model each sub-domain using a modular ontology and encapsulate the interdependence between them using a set of rules. Moreover, qualitative likelihood is assigned to each rule by domain experts (e.g. civil engineers) to encode the uncertainty of knowledge, and an inference engine is applied to predict the potential consequences of a given trigger with location specific data and the encoded rules. A web-based prototype system has been developed based on the above concept and demonstrated to a wide range of stakeholders. The system can assist in the process of decision making by aiding data collation and integration, as well as presenting potential consequences of possible triggers, advising on whether additional information is needed or suggesting ways of obtaining such information. The work shows an intelligent approach to integrate and process multi-source data to pioneer a novel way to aid a complex decision process with a high social impact. |
| first_indexed | 2025-11-14T20:41:35Z |
| format | Article |
| id | nottingham-60823 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:41:35Z |
| publishDate | 2020 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-608232020-06-11T00:37:45Z https://eprints.nottingham.ac.uk/60823/ A decision support system for urban infrastructure inter-asset management employing domain ontologies and qualitative uncertainty-based reasoning Wei, Lijun Du, Heshan Mahesar, Quratul-ain Al Ammari, Kareem Magee, Derek R. Clarke, Barry Dimitrova, Vania Gunn, David Entwisle, David Reeves, Helen Cohn, Anthony G. Urban infrastructure assets (e.g. roads, water pipes) perform critical functions to the health and well-being of society. Although it has been widely recognised that different infrastructure assets are highly interconnected, infrastructure management in practice such as planning, installation and maintenance are often undertaken by different stakeholders without considering these dependencies due to the lack of relevant data and cross-domain knowledge, which may cause unexpected cascading social, economic and environmental effects. In this paper, we present a knowledge based decision support system for urban infrastructure inter-asset management. By considering various infrastructure assets (e.g. road, ground, cable), triggers (e.g. pipe leaking) and potential consequences (e.g. tra c disruption) as a holistic system, we model each sub-domain using a modular ontology and encapsulate the interdependence between them using a set of rules. Moreover, qualitative likelihood is assigned to each rule by domain experts (e.g. civil engineers) to encode the uncertainty of knowledge, and an inference engine is applied to predict the potential consequences of a given trigger with location specific data and the encoded rules. A web-based prototype system has been developed based on the above concept and demonstrated to a wide range of stakeholders. The system can assist in the process of decision making by aiding data collation and integration, as well as presenting potential consequences of possible triggers, advising on whether additional information is needed or suggesting ways of obtaining such information. The work shows an intelligent approach to integrate and process multi-source data to pioneer a novel way to aid a complex decision process with a high social impact. 2020-11-15 Article PeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/60823/1/eswa_source_pdf_2020.pdf Wei, Lijun, Du, Heshan, Mahesar, Quratul-ain, Al Ammari, Kareem, Magee, Derek R., Clarke, Barry, Dimitrova, Vania, Gunn, David, Entwisle, David, Reeves, Helen and Cohn, Anthony G. (2020) A decision support system for urban infrastructure inter-asset management employing domain ontologies and qualitative uncertainty-based reasoning. Expert Systems with Applications, 158 . p. 113461. ISSN 09574174 Smart cities； Infrastructure maintenance；Underground utilities；Rule-based system；Reasoning under uncertainty http://dx.doi.org/10.1016/j.eswa.2020.113461 doi:10.1016/j.eswa.2020.113461 doi:10.1016/j.eswa.2020.113461 |
| spellingShingle | Smart cities； Infrastructure maintenance；Underground utilities；Rule-based system；Reasoning under uncertainty Wei, Lijun Du, Heshan Mahesar, Quratul-ain Al Ammari, Kareem Magee, Derek R. Clarke, Barry Dimitrova, Vania Gunn, David Entwisle, David Reeves, Helen Cohn, Anthony G. A decision support system for urban infrastructure inter-asset management employing domain ontologies and qualitative uncertainty-based reasoning |
| title | A decision support system for urban infrastructure inter-asset management employing domain ontologies and qualitative uncertainty-based reasoning |
| title_full | A decision support system for urban infrastructure inter-asset management employing domain ontologies and qualitative uncertainty-based reasoning |
| title_fullStr | A decision support system for urban infrastructure inter-asset management employing domain ontologies and qualitative uncertainty-based reasoning |
| title_full_unstemmed | A decision support system for urban infrastructure inter-asset management employing domain ontologies and qualitative uncertainty-based reasoning |
| title_short | A decision support system for urban infrastructure inter-asset management employing domain ontologies and qualitative uncertainty-based reasoning |
| title_sort | decision support system for urban infrastructure inter-asset management employing domain ontologies and qualitative uncertainty-based reasoning |
| topic | Smart cities； Infrastructure maintenance；Underground utilities；Rule-based system；Reasoning under uncertainty |
| url | https://eprints.nottingham.ac.uk/60823/ https://eprints.nottingham.ac.uk/60823/ https://eprints.nottingham.ac.uk/60823/ |