Current studentsExisting staffContact us
 

Closing the existing circularity gap in the building construction industry using artificial intelligence: A systematic review of literature

Simple item page
dc.contributor.authorOluleye, B.I.
dc.contributor.authorChan, D.W.M.
dc.contributor.authorAntwi-Afari, P.
dc.contributor.conferenceAustralian Universities Building Education Association Annual Conference (AUBEA) (23 Nov 2022 - 25 Nov 2022 : Western Sydney University)
dc.contributor.editorPerera, S.
dc.contributor.editorHardie, M.
dc.date.issued2022
dc.description.abstractGiven that each construction infrastructure project is unique, it is necessary to perform a Job Hazard Analysis (JHA) for all high-risk activities in every construction project. Due to the dynamic nature of construction sites, JHA needs to be conducted before the job and then updated when new information is added. In most cases, JHA is performed manually, and it is challenging to reflect the changes in the construction plans or schedules in JHAs. Considering these challenges associated with JHA practices,previous researchers attempted to automate the JHA process by building ontology-based solutions.However, most of these studies have only considered the explicit knowledge of JHA and ignored the implicit knowledge for hazard identification and control, which is considered as one of the most important knowledge components in the process of JHA. Thus, this research attempts to represent theJHA knowledge based on both the explicit and implicit knowledge of JHA in a form of ontology, focusing on water infrastructure jobs. To achieve this goal, a document analysis on JHA documents and a qualitative Delphi method were adopted to identify the implicit and explicit concepts and relationships regarding the identification and control of various hazards from the practitioners. This paper provides the concepts related to JHA and the relationships among them that can be mapped onto an ontology for automating JHA processes.
dc.identifier.citationGlobal Challenges in a Disrupted World: Smart, Sustainable and Resilient Approaches in the Built Environment, 2022 / Perera, S., Hardie, M. (ed./s), pp.747-756
dc.identifier.doi10.26183/a6pq-mg06
dc.identifier.orcidAntwi-Afari, P. [0000-0003-2966-9325]
dc.identifier.urihttps://hdl.handle.net/11541.2/33138
dc.language.isoen
dc.publisherWestern Sydney University
dc.publisher.placeOnline
dc.rightsCopyright 2022. Copyright in individual articles contained in the Proceedings of the AUBEA 2022 Conference is vested in each of the authors. No reproduction, copy or transmission may be made without written permission from the individual authors
dc.source.urihttps://doi.org/10.26183/a6pq-mg06
dc.subjectconceptualisation
dc.subjectjob hazard analysis
dc.subjectontology
dc.subjectsafety management
dc.subjectwater infrastructure
dc.titleClosing the existing circularity gap in the building construction industry using artificial intelligence: A systematic review of literature
dc.typeConference paper
pubs.publication-statusPublished online
ror.fileinfo12259650130001831 13259650120001831 Ontology based representation
ror.mmsid9916721816201831

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Ontology based representation.pdf
Size:
917.19 KB
Format:
Adobe Portable Document Format
Description:
Published version
Download

Collections