Project completed in 2023
Level: Ph.D.
Areas of research : Artificial intelligence, Digital twin.

Development of a framework for the implementation of BIM-based reduced reality in the AEC-FM industry

Abstract

This research project aims to create a framework for the integration of building information modeling (BIM) with reduced reality (DR) in the architecture, engineering, construction and facilities management (AEC-FM) sector. Reduced reality is a real-time technique that visually removes unwanted physical objects and improves visualizations in augmented reality (AR) scenarios. Although BIM and DR have both attracted attention individually, their synergistic potential remains underexplored. This research aims to fill this gap by establishing a robust framework that harnesses the data management, visualization and information-rich capabilities of BIM to enhance DR applications. This framework will be designed to enhance monitoring, management and planning tasks within the AEC-FM, offering an innovative approach to real-time visualization and information retrieval. By providing a structured methodology and insight into the practical challenges and benefits, this thesis helps advance the adoption of BIM-based DR in the AEC-FM industry.

Areas of research : Artificial intelligence, Digital twin.
Key words : Augmented reality, BIM, Computer vision, Data integration, Digital twins.

Project results

In this thesis, we have obtained several significant research results and we also anticipate other expected results: 1. BIM-based DR framework: The development of a framework for the integration of Building Information Modeling (BIM) with Reduced Reality (DR) in the Architecture, Engineering, Construction and Facilities Management (AEC-FM) industry has been successfully completed. This framework serves as a structured approach to combining these technologies seamlessly, enabling real-time object removal and enhanced visualizations. 2. Improved real-time visualization: The framework has significantly enhanced visualization capabilities in the AEC-FM sector, resulting in more accurate and detailed visual representations of construction sites and installations. This progress contributes to improved decision-making, monitoring and planning processes.
3. Practical applications: The research identified and explored various practical applications of BIM-based DR in the AEC-FM industry. These applications cover a wide range of tasks, including construction project monitoring, facilities management, landscaping and more. The successful implementation of this technology has brought practical solutions to long-standing challenges in the industry, improving efficiency, safety and precision in a variety of tasks. 4. Future results: The integration of artificial intelligence (AI) and digital twins represents the next frontier of our research. By incorporating AI algorithms and harnessing the power of digital twins, we aim to further enhance the capabilities of our BIM-based reduced-reality framework.

Project contributions

This study will advance understanding of DR as a new visualization technique by exploring the literature on DR and demonstrating how different methods can be used in a variety of applications. The other contribution will be to explore the benefits of BIM as the primary source of digital information about physical environments to aid DR in rendering and retrieving background information. In the industrial context, this research offers practical solutions to long-standing challenges. Identifying and exploring diverse applications for BIM-based DR provides AEC-FM professionals with tangible tools to improve real-time monitoring, planning and management tasks.

Publications

Publications from this project are available below:

Eskandari, Roghieh; Motamedi, Ali, Diminished Reality in Architectural and Environmental design: Literature Review of Techniques, Applications, and Challenges. 38th International Symposium on Automation and Robotics in Construction (ISARC 2021).

Eskandari, Roghieh; Motamedi, Ali, Visibility Enhancement of Crane Operators Using BIM-Based Diminished Reality. 23rd International Conference on Construction Applications of Virtual Reality (CONVR 2023).

Research team

The project team :

Ali Motamedi
Team

The project team

Ali Motamedi
Partners

This project was supported by :

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