Automated cost and carbon estimation using artificial intelligence techniques

M. Georgioudakis, A. Zghari, A. Chatzisymeon, B. Haraszti (2021). Automated cost and carbon estimation using artificial intelligence techniques. Project Controls 2021. Technical Paper.

Abstract:The global construction industry is currently very inefficient in assessing thecapital costs and CO2 footprint of proposed projects, during thepreconstruction phase. This fact leads to inefficient cost and CO2 data captureand assessment for the whole life cycle of projects. Assessing multiplealternative designs and construction methods to optimise cost and embodied CO2of projects is currently a manual, and time consuming, process that projectstakeholders cannot afford due to time constraints. There is a general trend touse technology to automate this process by developing a standardised datastructure within the 3D design models, such as Uniclass classification, whichcan enable automated quantity take-offs through its mapping with regionalstandard methods of measurement for cost planning. In this work, we propose theimplementation of a new automation tool that enables construction projects toleverage the full benefits of building information modelling in combinationwith artificial intelligence techniques for Cost and CO2 estimates. Thisapproach leads to shorter pre-construction phases, reduced project managementcosts, faster turnaround times for optioneering and value engineering, greatervisibility of carbon emissions and overall improved cost & carbon control.