TY  - CONF
TI  - Embedded machine learning as an enabler of lean construction
C1  - Singapore, Singapore
C3  - Proceedings of the 34th Annual Conference of the International Group for Lean Construction (IGLC 34)
SP  - 132
EP  - 142
PY  - 2026
DO  - 10.24928/2026/0206
AU  - Vauk, Björn Bernhard
AU  - Mentrup, Lars Eric
AU  - Enge, Felix Archibald
AD  - PhD Candidate, Institute for Production Technology and Systems (IPTS), Leuphana University Lüneburg, Germany, bjoern.vauk@leuphana.de, orcid.org/0009-0006-3464-3049
AD  - PhD Candidate, TU Berlin, Germany, lars.mentrup@projekte.g-wt.de, orcid.org/0009-0000-2270-5667
AD  - Dr.-Ing., CEO, Makeo, Germany, felix.enge@thesixpractice.de, orcid.org/0009-0006-5605-646X
ED  - Hamzeh, Farook
ED  - Poshdar, Mani
ED  - Garcia-Lopez,, Nelly P.
AB  - Lean Construction aims to continuously improve construction processes through consistent alignment with customer value. Accordingly, research indicates the necessity of objective and scalable methods for the continuous capture of construction processes. Manual observations enable in-depth contextual analysis but produce discontinuous and sample-based data. Observer-independent measurement approaches for continuous acquisition of time expenditures per construction activity support the provision of scalable data across workers, work packages, shifts, trades, and construction projects.
To address this need, an approach is presented for automated recognition of construction activities using embedded machine learning. In a painting trade case study, a single wrist-worn sensor system classifies main activities at 6 s intervals, achieving an accuracy of 96.4 %. Time-series analysis under open-set site conditions consistently aggregates activity sequences, validated against video-based ground truth. This enables the reconstruction of chronological process sequences and their quantification in terms of time expenditures per activity.
This approach can make production flow observable, support the assessment of performance targets within work packages and takts and the analysis of trade-offs between flow and resource efficiency. Linking activity-based time expenditures with construction outputs may support the derivation of labour consumption rates and thereby contribute to the implementation of Lean Construction in construction management.
KW  - Lean construction
KW  - process
KW  - production
KW  - work flow
KW  - AI.
PB  - 
T2  - Proceedings of the 34th Annual Conference of the International Group for Lean Construction (IGLC 34)
DA  - 2026/06/22
CY  - Singapore, Singapore
L1  - http://iglc.net/Papers/Details/2509/pdf
L2  - http://iglc.net/Papers/Details/2509
N1  - Export Date: 19 June 2026
DB  - IGLC.net
DP  - IGLC
LA  - English
ER  -