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Towards a Quantitative Approach for Monitoring and Evaluating Construction Defect Management Inspection Performance using Eye-tracking Technologies

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dc.contributor.authorMay, K.W.
dc.contributor.authorJing, A.
dc.contributor.authorWalsh, J.
dc.contributor.authorSmith, R.T.
dc.contributor.authorGu, N.
dc.contributor.authorThomas, B.H.
dc.contributor.conference21st IEEE International Symposium on Mixed and Augmented Reality (ISMAR) (17 Oct 2022 - 22 Oct 2022 : SINGAPORE, Singapore)
dc.date.issued2022
dc.description.abstractDefect management (DM) inspections play an important role in the overall performance of construction projects. Identifying defects early within the construction project life cycle leads to mitigating significant reworks and potential hazards from occurring later in the building life cycle. Despite the importance of DM inspections in construction, currently, minimal approaches exist to evaluate or assess the performance quality of on-site DM inspectors. To address these issues, we present a novel data analysis tool that incorporates Building Information Modelling technologies to evaluate DM in-spection performance using eye gaze data captured during the DM inspection. This paper presents an overview of our proposed data analysis tool, which consists of a four-dimensional (4D) playback visualisation system and a quantitative data analysis simulator. We also present our findings from a pilot study that uses our proposed data analysis tool to comparatively evaluate the performance of two types of DM inspection approaches: conventional paper-based methods, and an experimental Augmented Reality (AR) system. We release our DM data analysis software as an open-source project under the MIT license.
dc.identifier.citationProceedings 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct Ismar Adjunct 2022, 2022, pp.776-781
dc.identifier.doi10.1109/ISMAR-Adjunct57072.2022.00165
dc.identifier.isbn9781665453653
dc.identifier.issn2771-1102
dc.identifier.issn2771-1110
dc.identifier.orcidWalsh, J. [0000-0002-4822-990X]
dc.identifier.urihttps://hdl.handle.net/11541.2/32418
dc.language.isoen
dc.publisherIEEE COMPUTER SOC
dc.publisher.placeUS
dc.relation.ispartofseriesIEEE International Symposium on Mixed and Augmented Reality Workshops
dc.rightsCopyright 2022 IEEE Access Condition Notes: Accepted manuscript is available open access
dc.source.urihttps://doi.org/10.1109/ISMAR-Adjunct57072.2022.00165
dc.subjectdefect management inspections
dc.subjectbuilding information modelling
dc.subjectconstruction
dc.subjectdata analysis
dc.subjecteye tracking
dc.subjectaugmented reality
dc.titleTowards a Quantitative Approach for Monitoring and Evaluating Construction Defect Management Inspection Performance using Eye-tracking Technologies
dc.typeConference paper
pubs.publication-statusPublished
ror.fileinfo12299273030001831 13306239360001831 9916714029901831
ror.mmsid9916714029901831

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