TY  - CONF
TI  - Smart Data - Dealing With Task Complexity in Construction Scheduling
AU  - Oprach, Svenja
AU  - Steuer, Dominik
AU  - Krichbaum, Viktoria
AU  - Haghsheno, Shervin
AD  - Research fellow, Karlsruhe Institute of Technology, Germany, +49-721-608-43650, svenja.oprach@kit.edu
AD  - Research fellow, Karlsruhe Institute of Technology, Germany, +49-721-608-44122, dominik.steuer@kit.edu
AD  - M. Sc. Student, Karlsruhe Institute of Technology, Germany, +49-721-608-43650, svenja.oprach@kit.edu
AD  - Professor, Karlsruhe Institute of Technology, Germany, +49-721-608-42646, shervin.haghsheno@kit.edu
PY  - 2019
DA  - 2019/07/03
T2  - Proc. 27th Annual Conference of the International Group for Lean Construction (IGLC)
C3  - Proc. 27th Annual Conference of the International Group for Lean Construction (IGLC)
CY  - Dublin, Ireland
SP  - 347
EP  - 358
DO  - 10.24928/2019/0155
SN  - 2309-0979 (ISSN)
AB  - 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.
KW  - Knowledge management
KW  - Smart Data
KW  - construction planning
KW  - digitalization
KW  - data analytics
L1  - https://www.iglc.net/papers/details/1649/pdf
UR  - https://www.iglc.net/papers/details/1649
DB  - IGLC.net
LA  - English
N1  - Export date: 04 October 2026
ER  -