Application of a Multi-disciplinary Collaborative Platform Based on GIS and BIM Data Integration in Smart Building Design: Optimization of Construction Planning and Maintenance Management Supported by Big Data and Machine Learning
Year: 2025
Type: article
Abstract: In this study, a multi-source collaborative platform integrating geographic information system and building information model is constructed to solve the technical bottleneck of intelligent building life cycle management through an interdisciplinary data integration mechanism. The platform uses big data mining and machine learning technology to verify its breakthrough value in design optimization, construction collaboration, and operation and maintenance decision-making in simulated urban complex development scenarios. Empirical data show that the construction team using dynamic data cockpit has significantly improved the efficiency of process connection, the equipment idle rate has decreased by about 18% compared with the traditional mode, and the cost of rework change has been reduced by nearly 30%. A typical case analysis reveals that the platform's unique heterogeneous data fusion engine can effectively solve the problem of information island in multi-professional collaboration, and the intelligent early warning module developed by it has achieved a breakthrough in the structural safety monitoring industry with a false alarm rate of less than 2.5%. This technical solution has been authorized by five invention patents in the field of housing construction, and its core architecture is the verification of large-scale applications in three smart park projects in the Yangtze River Delta region.
Authors: Siyang Huang, Yuchen Wang, Jian Jin
Institutions: Universiti Putra Malaysia, University of South Florida
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409237152