INCORPORATION OF CONTEXT-BASED DATA TO REFINE MACHINE LEARNING MODELS IN INDUSTRIALIZED CONSTRUCTION

Melgar M.; Miranda Y.; Al-Hussein M.; Barkokebas B. · Proceedings of the European Conference on Computing in Construction (2025) · DOI: 10.35490/ec3.2025.381

Resumen

Industrialized construction promises to transform the industry by performing activities in shop floors to improve operational efficiency. However, the lack of integration between practical experience and real-time data limits more efficient operations on the shop floor. This study addresses this limitation by combining design parameters from BIM models with real-time production data collected via RFID in a semi-automated shop floor. By including context-based data in machine learning models, cycle time prediction accuracy was improved, compared to models containing only design-based data. highlighting how data granularity optimizes operational planning and production processes in Industrialized Construction.

Instituciones: Universidad Nacional de Ingeniería