Application of computer vision for construction progress monitoring: a qualitative investigation

dc.contributor.authorMoragane, HPMNLB
dc.contributor.authorPerera, BAKS
dc.contributor.authorPalihakkara, AD
dc.date.accessioned2023-06-21T09:40:38Z
dc.date.available2023-06-21T09:40:38Z
dc.date.issued2022
dc.description.abstractProgress monitoring of construction work is crucial to identify the discrepancies between the as-built product and as-planned design and take necessary action based on the results. Construction work is time consuming and labour intensive. However, the use of new technologies, such as computer vision (CV), in construction progress monitoring (CPM) can minimise human errors. Thus, the aim of this study was to explore the current applications of CV in the construction industry in general and in the different stages of CPM. A qualitative approach based on the Delphi technique comprising two interview rounds was used to collect the required data. The study findings revealed that CPM has seven stages: initial planning, data acquisition, information retrieval, verification, progress estimation and comparison, results visualisation and schedule updating. During these stages, CV can be used in various CPM activities, such as earthmoving operations, crane operations, formwork and rebar tracking, worker activity tracking, safety assurance, landscape identification, work item monitoring and integrating with other technologies. Familiarisation of the workforce with CV and research on the applications of CV in construction can help the construction industry to move with technology and be on par with other industries. This study would enable construction personnel to explore the possibility of applying CV in CPM. Further research on identifying the synergy between CV and CPM can be based on the study findings.en_US
dc.identifier.citationMoragane, H. P. M. N. L. B., Perera, B. A. K. S., Palihakkara, A. D., & Ekanayake, B. (2022). Application of computer vision for construction progress monitoring: A qualitative investigation. Construction Innovation, 125-137. https://doi.org/10.1108/CI-05-2022-0130en_US
dc.identifier.databaseEmeralden_US
dc.identifier.doihttps://doi.org/10.1108/CI-05-2022-0130en_US
dc.identifier.issn1471-4175en_US
dc.identifier.journalConstruction Innovationen_US
dc.identifier.pgnos125-137
dc.identifier.urihttp://dl.lib.uom.lk/handle/123/21142
dc.identifier.year2022en_US
dc.language.isoenen_US
dc.subjectConstruction Work Progress Monitoringen_US
dc.subjectComputer Visionen_US
dc.subjectStages of Progress Monitoringen_US
dc.titleApplication of computer vision for construction progress monitoring: a qualitative investigationen_US
dc.typeArticle-Full-texten_US

Files