Ontology-Based Semantic Construction Image Interpretation

dc.contributorAalto Universityen
dc.contributor.authorZheng, Yuanen_US
dc.contributor.authorKhalid Masood, Mustafaen_US
dc.contributor.authorSeppänen, Ollien_US
dc.contributor.authorTörmä, Seppoen_US
dc.contributor.authorAikala, Anttien_US
dc.contributor.departmentDepartment of Civil Engineeringen
dc.contributor.groupauthorPerformance in Building Design and Constructionen
dc.descriptionFunding Information: This research was funded by the ACTOR project of Business Finland’s Low Carbon Built Environment Program that receives funding from EU’s Recovery and Resilience Facility (from 2022 onward) and the Building 2030 consortium of 21 Finnish companies (until 2021). Publisher Copyright: © 2023 by the authors.
dc.description.abstractImage-based techniques have become integral to the construction sector, aiding in project planning, progress monitoring, quality control, and documentation. In this paper, we address two key challenges that limit our ability to fully exploit the potential of images. The first is the “semantic gap” between low-level image features and high-level semantic descriptions. The second is the lack of principled integration between images and other digital systems used in construction, such as construction schedules and building information modeling (BIM). These challenges make it difficult to effectively incorporate images into digital twins of construction (DTC), a critical concept that addresses the construction industry’s need for more efficient project management and decision-making. To address these challenges, we first propose an ontology-based construction image interpretation (CII) framework to formalize the interpretation and integration workflow. Then, the DiCon-SII ontology is developed to provide a formalized vocabulary for visual construction contents and features. DiCon-SII also acts as a bridge between images and other digital systems to help construct an image-involved DTC. To evaluate the practical application of DiCon-SII and CII in supporting construction management tasks and as a precursor to DTC, we conducted a case study involving drywall installation. Via this case study, we demonstrate how the proposed methods can be used to infer the operational stage of a construction process, estimate labor productivity, and retrieve specific images based on user queries.en
dc.description.versionPeer revieweden
dc.identifier.citationZheng, Y, Khalid Masood, M, Seppänen, O, Törmä, S & Aikala, A 2023, ' Ontology-Based Semantic Construction Image Interpretation ', Buildings, vol. 13, no. 11, 2812 . https://doi.org/10.3390/buildings13112812en
dc.identifier.otherPURE UUID: 774605e0-fbf6-4f4a-9536-dcf656cc04d7en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/774605e0-fbf6-4f4a-9536-dcf656cc04d7en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85178384870&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/130670981/buildings-13-02812.pdfen_US
dc.publisherMDPI AG
dc.relation.ispartofseriesVolume 13, issue 11en
dc.subject.keyworddigital twin construction (DTC)en_US
dc.subject.keywordsemantic image interpretation (SII)en_US
dc.titleOntology-Based Semantic Construction Image Interpretationen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi