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EXPORT DATE: 19 April 2024

@CONFERENCE{Oprach2019,
author={Oprach, Svenja and Steuer, Dominik and Krichbaum, Viktoria and Haghsheno, Shervin },
editor={ },
title={Smart Data - Dealing With Task Complexity in Construction Scheduling}, 
journal={Proc. 27th Annual Conference of the International Group for Lean Construction (IGLC)}, 
booktitle={Proc. 27th Annual Conference of the International Group for Lean Construction (IGLC)}, 
year={2019},
pages={347-358},
url={http://www.iglc.net/papers/details/1649},
doi={10.24928/2019/0155},
affiliation={Research fellow, Karlsruhe Institute of Technology, Germany, +49-721-608-43650, svenja.oprach@kit.edu ; Research fellow, Karlsruhe Institute of Technology, Germany, +49-721-608-44122, dominik.steuer@kit.edu ; M. Sc. Student, Karlsruhe Institute of Technology, Germany, +49-721-608-43650, svenja.oprach@kit.edu ; Professor, Karlsruhe Institute of Technology, Germany, +49-721-608-42646, shervin.haghsheno@kit.edu },
abstract={Due to the numerous influencing factors, construction scheduling is a complex task. As construction projects are having a unique character, scheduling takes time and often uses high time buffers to cover uncertainties. Using historic project data with artificial intelligence applications show potentials to support valid and simple scheduling in the future. The construction industry already deals with large volumes of heterogeneous data and the amount of data is expected to increase exponentially with the Internet of Things (IoT). Smart data filters and analyses big data for useful information and creates a subset of information that is important and valuable. Therefore smart data sets a data management structure according to the lean principles. Due to fragmented data management practices and a misunderstanding of the needed information in construction, data management practices in construction projects are far behind other industries. By adapting existing applications of artificial intelligence to construction scheduling, the gap of data management practices gets more visible. This paper identifies in three case studies relevant data (smart data) in and current challenges for construction scheduling based on historic data. Further research is needed to close the existing gap in construction data management. },
author_keywords={Knowledge management, Smart Data, construction planning, digitalization, data analytics },
address={Dublin, Ireland },
issn={2309-0979 },
publisher={ },
language={English},
document_type={Conference Paper},
source={IGLC},
}