Development and testing of an automated time-motion detector for construction activities

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dc.contributor.advisorWium, Janen_ZA
dc.contributor.advisorJurgens, Chrisen_ZA
dc.contributor.authorMeyer, Ewald Mauritzen_ZA
dc.contributor.otherStellenbosch University. Faculty of Engineering. Dept. of Civil Engineering.en_ZA
dc.date.accessioned2024-02-27T08:48:27Zen_ZA
dc.date.accessioned2024-04-26T12:39:51Zen_ZA
dc.date.available2024-02-27T08:48:27Zen_ZA
dc.date.available2024-04-26T12:39:51Zen_ZA
dc.date.issued2024-02en_ZA
dc.descriptionThesis (MEng)--Stellenbosch University, 2024.en_ZA
dc.description.abstractENGLISH ABSTRACT: This study looked into the intricacies of construction rework and the methods that have been used to identify, quantify and manage rework. From this research, a novel process of combining equipment, software and methodology is presented in the development of a concept of an automated time-motion detector system, with a proposed method to implement the system to quantify rework of structural elements on construction sites. The aim of this study is to develop and test a technological solution to detect time spent on construction activities and ultimately uncover un-announced rework on construction sites. This is achieved by completing the following objectives: (i) Determine the most feasible technological solution for the time-motion monitoring of construction activities that could lead to quality failures. (ii) Develop a time-motion detector that can be used to monitor construction activities remotely. (iii) Implement and test the system by performing simplified tests in a controlled environment to determine the accuracy of the system. (iv) Discuss results and future implementations. The motivation for this study was based on the challenge of efficient construction management and the inability to learn from quality failures on construction sites resulting from a lack of suitable data and documentation relating to the execution of construction activities. This lack of execution information hinders construction companies to become more efficient and profitable. In research, a shift is seen towards the gathering and analysis of data to improve the efficiency and profitability of construction companies after very successful implementation of data analysis and management in other fields of study. In this study, a proof of concept of an automated time-motion detector was developed in Python to record and analyse construction activities to determine the human capital required for these activities. The system was tested with several trial tests, where it was found that the system has an average accuracy of 84% while valuable operational data, limitations and recommendations for the use of this system were obtained.en_ZA
dc.description.abstractAFRIKAANSE OPSOMMING: Hierdie studie het die ingewikkeldhede van herwerk en die metodes wat gebruik is om herwerk te kwantifiseer en te bestuur ondersoek. Uit hierdie navorsing word n nuwe kombinasie van toerusting, sagteware en metodes voorgelê vir die gebruik van n konsep van 'n geoutomatiseerde tydbewegingswaarnemingstelsel, met 'n voorgestelde metode om die stelsel te implementeer wat herbewerking van strukturele elemente op konstruksieterreine kwantifiseer. Die doel van hierdie studie is om n tegnologiese oplossing te ontwikkel om die tyd wat op konstruksie aktiwiteite spandeer word te bepaal en uiteindelik onaangekondigde herwerk op konstruksie terreine te identifiseer. Die volgende mikpunte is gebruik om die doelwit te bereik : (i) Bepaal die mees haalbare tegnologiese oplossing vir die tyd-beweging monitering van konstruksie aktiwiteite wat kan lei tot kwaliteit mislukkings. (ii) Ontwikkel 'n tydbewegingswaarnemingstelsel wat gebruik kan word om konstruksie-aktiwiteite op afstand te monitor. (iii) Implementeer en toets die stelsel deur vereenvoudigde toetse in 'n beheerde omgewing uit te voer om die akkuraatheid van die stelsel te bepaal. (iv) Bespreek resultate en toekomstige implementerings. Die motivering vir hierdie studie was gebaseer op die uitdaging van doeltreffende konstruksiebestuur en die onvermoë om te leer uit kwaliteitsmislukkings op konstruksieterreine sonder voldoende data en dokumentasie met betrekking tot die uitvoering van konstruksieaktiwiteite. Hierdie gebrek aan uitvoeringsinligting verhinder konstruksiemaatskappye om meer doeltreffend en winsgewend te word. In navorsing is daar 'n verskuiwing na die insameling en ontleding van data om die doeltreffendheid en winsgewendheid van konstruksiemaatskappye te verbeter, na baie suksesvolle implementering van data-analise en -bestuur in ander studierigtings. In hierdie studie is 'n bewys van konsep van 'n outomatiese tydbewegingswaarnemingstelsel in Python ontwikkel om konstruksieaktiwiteite aan te teken en te ontleed om die menslike kapitaal wat vir hierdie aktiwiteite benodig word, te bepaal. Die stelsel is met verskeie proeflopies getoets, waar gevind is dat die stelsel 'n gemiddelde akkuraatheid van 84% het, terwyl waardevolle operasionele data, beperkings en aanbevelings vir die gebruik van hierdie stelsel verkry is.af_ZA
dc.description.versionMastersen_ZA
dc.format.extent148 pages : illustrationsen_ZA
dc.identifier.urihttps://scholar.sun.ac.za/handle/10019.1/130302en_ZA
dc.language.isoen_ZAen_ZA
dc.language.isoen_ZAen_ZA
dc.publisherStellenbosch : Stellenbosch Universityen_ZA
dc.rights.holderStellenbosch Universityen_ZA
dc.subject.lcshConstruction industry -- Automationen_ZA
dc.subject.lcshMotion detectorsen_ZA
dc.subject.lcshBuilding information modelingen_ZA
dc.subject.lcshComputer visionen_ZA
dc.titleDevelopment and testing of an automated time-motion detector for construction activitiesen_ZA
dc.typeThesisen_ZA
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