Big Data and Machine Learning-enabled Automated BIM for Projects (Auto-BIM): A Common Data Collaborative System for Improved Project Performance

Project: Research

Project Details


The research to be carried out is divided into 13 Work-Packages (WP). The WPs are as described below:

WP1 - Further Stakeholder Expert Workshops: This WP involves further workshops with key stakeholders to elicit wider domain knowledge in addition to the stakeholder's consultation done before writing this proposal. The milestone to be achieved at the end of this WP is a robust data collection methodology and stakeholder engagement report.

WP2 - Development of Project Implementation Frameworks: This WP includes the review of extant literature on machine learning algorithms, BIM Protocols, BIM Standards and Big data analytics for automated naming and population of building information. This will culminate in the development of a theoretical and conceptual framework for project implementation

WP3 - Development of Real-time Cloud-based Common Data Environment (CDE): This WP is for the development of a cloud-based CDE for data aggregation and storage. It involves the development of a database for structured data
collection, CDE development and implementation of common data server functionalities

WP4 - Case Identification, Analysis and Scenario Modelling: This WP involves an analysis of BIM models for training the Machine Learning algorithms. It involves identification of existing models, development of new models and linkage to the CDE.

WP5 - Creation of Real-time Big Data Analytics Platform for Deep-Learning. This WPs involves the configuration of big data development environment and the development of Deep Learning Models for automating building information.

WP6 - Development of the Auto-BIMName Application Platform: This WP involves the development of the system platform for facilitating automated files, elements and component naming in line with PAS-1192 and BS EN ISO 19650. This is the first component of the Auto-BIM software system and it involves the use of big data analytics and machine learning algorithms to support automated file naming in a CDE.

WP 7 - Development of the Auto-BIMPopulate/Share Application Platform : This WP involves the development of the system platform for (I) automated population of 3D representation of products and Building elements with relevant
metadata including the Omniclass classification, model number, service information, materials, etc. (ii)sharing BIM-objects and associated information; (iii)comparing cost/carbon. The WP combines the development of the second and third component of the Auto-BIM system.

WP 8 - Development of the Auto-BIMLearn Application Platform: This WP involves the development of the system platform for facilitating BIM Model learning from previous project design, construction, asset management, and decommissioning information. This would be facilitated by the underlying lesson learnt from previous projects as well as historic project data.

WP9 - Auto-BIM Full System Prototyping: This WP involves the development and testing of the proposed system architecture as well as its linkage to the deep learning models, Auto-BIMName, Auto-BIMPopulate, Auto-BIMLearn and the

WP10 - Software development and Full System Integration and Testing: This WP is for the integration of all the platformsinto a single system.

WP11 - System Testing using Real-life Case-Studies: Final testing in a real-world environment will be carried out in this WP

WP12 - Exploitation and Dissemination: The WP will capture all dissemination and product exploitation activities, including academic publications, market exploitation and setting up of a spin-out company

WP13 - Project Management: This WP is for the overall project coordination and management over the entire project duration.
Short titleAuto BIM
Effective start/end date1/01/1931/12/20


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