The innovative potential of Generative Pre-trained Transformers (GPTS) for quality inspections in Swedish construction projects
Paper in proceeding, 2024

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.

cloud service

Quality control

self-checks

Swedish construction projects

generative pre-trained transformer (GPT)

Author

Dimosthenis Kifokeris

Chalmers, Architecture and Civil Engineering, Building Design

Jan Kohvakka

Incoord Installationscoordinator

Christian Koch

University of Southern Denmark

Halmstad University

Donia Aslanzadeh

Robert Dicksons stiftelse

Proceedings of the European Conference on Computing in Construction

26841150 (eISSN)

Vol. 2024 829-836 231
978-9-083451-30-5 (ISBN)

European Conference on Computing in Construction, EC3 2024
Chania, Greece,

A cloud service with GPT-based project support for quality assurance in construction projects for clients, engineers, and contractors

Formas (2023-00111), 2023-05-01 -- 2024-08-31.

Subject Categories

Construction Management

DOI

10.35490/EC3.2024.231

More information

Latest update

9/20/2024