Machine learning-integrated 5D BIM informatics: building materials costs data classification and prototype development

Abstract Non-informatics cost estimation is a tedious process and requires substantial amount of time manual operations. However, BIM adoption approaches have attracted significant attention with this respect. Since models are object-based built-in parametric information, it easier to capture the quantities building elements deliver more accurate estimates less errors omissions. As most current standards designed developed based on old-fashioned construction project delivery systems, lack compatibility between their classification BIM-based informatics observed. This study, therefore, aims develop an framework integrate standard in order expedite 5D enhance digital transformation practices projects. The considered be new approach which can automatically estimate using machine learning-integrated algorithms MATLAB engine for its effective implementation.