The Innovative Potential of Generative Pre-Trained Transformers (GPTS) for Quality Inspections in Swedish Construction Projects

Dimosthenis Kifokeris1, Jan Kohvakka2, Donia Aslanzadeh3
1 Chalmers University of Technology, Gothenburg, Sweden
2 Incoord, Stockholm, Sweden
3 Robert Dicksons Stiftelse, Gothenburg, Sweden
DOI: 10.35490/EC3.2024.231
Abstract: Approaching quality inspection plans in Swedish construction projects as mere checklists and minimizing the clients’ involvement, can reduce their value. We propose improving this process through a cloud service concept for clients, designers, and contractors, utilizing generative pre-trained transformer (GPT) AI. Methodologically, we synthesize literature insights on GPT uses for construction, and empirical inquiries on developing a quality self-inspection service. We posit that through this service, project knowledge, known quality defects and lessons-learned from previous cases can be better accessed and shared – potentially leading to time savings, suggesting best practices, and improving the collaboration among clients, designers, and contractors.
Keywords: cloud service, generative pre-trained transformer (GPT), Quality Control, self-checks, Swedish construction projects

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