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Laing O'Rourke Centre for Construction Engineering and Technology

 
Computer Vision

Computers can increasingly gain high-level understanding from digital images or videos.

Formalizing the processes whereby computers acquire, handle, analyse and represent visual and spatial data will assist informed decision making during all stages of the infrastructure life cycle. This work covers the creation of digital representations of physical assets (digital twins) and the use of models and mixed reality technology to transform the design and management of infrastructure.

Project: Automatic Construction Monitoring Through Semantic Information Modelling

This project aims to develop computational algorithms and methods for automatic as-built construction monitoring through semantics-based Building Information Modelling (BIM). Construction as–built monitoring is crucial for the cost, time, quality and safety of projects. Methods for generating as-built status are primarily manual. There are gaps in sophistication of automation, and recognition for semantic construction information during the process is low. The project is expected to provide efficient and accurate solutions for as-built construction monitoring. The implementation of the as-build modelling approach will provide a significant tool to manage the status of construction project, including progress and quality tracking. [Further information]

Sponsor: Australian Research Council

Partners: Curtin University, Australia

Laing O’Rourke Centre involvement: Co-Principal Investigator Dr Ioannis Brilakis

Dates: April 2017 – March 2020

 

PhD Project: Top-down As-is Modelling of Industrial Facilities

This research will explore ways to detect existing building objects using spatial and visual data for the purpose of automating the generation of as-built geometric models of industrial facilities. The research will address both construction engineering and computer vision issues.

Researcher: Evangelia Agapaki

Supervisor: Dr Ioannis Brilakis

Funding: EPSRC (DTP) and AVEVA

Dates: October 2016 – September 2020

 

PhD Project: Automated BIM Generation of Existing and Under Construction Railways

This research is aimed at creating a viable approach to automate the generation of as-is geometric railway Building Information Modelling (BIM).The key novel idea that makes this possible is that railways follow a set of engineering design assumptions which can be used as guides for segmentation by Markov Chain Monte Carlo (MCMC) methods, region growing, or octrees.

Researcher: Mahendrini Fernando Ariyachandra

Supervisor: Dr Ioannis Brilakis

Funding: Bentley Systems UK Ltd, Cambridge Trust

Dates: October 2017 – September 2021

 

Project: Cloud-based Building Information Modelling

Building Information Modelling (BIM) as a product and process enables stakeholders across the built environment sector to create digital versions of real world assets (such as buildings, bridges and tunnels). The digital versions are commonly called 'digital twins'. When placed on the cloud, the digital twins can serve as a resilient and integrated repository of all asset data throughout their life-cycle. Such a repository is a key enabler in this sector of all upcoming IT waves, such as cloud computing, data analytics, participatory sensing, and smart infrastructure. The potential benefits have attracted interest from a wide array of end-users whose interests span from early design phases to operation and asset management, and from roads and bridges to industrial off-shore facilities. This has led to aggressive market penetration in the last decade. However, the full potential of BIM is currently exploited only in a fairly narrow range of applications. This is mainly due to the lack of trained scientific personnel capable of understanding the value of BIM and creating the link between digital twins and possible applications.
The ambition of CBIM is therefore to educate researchers in the development of a set of novel and disruptive BIM technologies that will automate the generation and enrichment of digital twins, improve the management, security and resilience of BIM-enabled processes, and boost the industrial uptake of BIM across sectors and disciplines by training these researchers to valorise and exploit their work. This new generation of researchers can play a key role in the widespread implementation of BIM products and processes dedicated to digitising our built infrastructure and managing our assets better to yield massive gains in sustainability, productivity and safety. [Further information]

Sponsor: European Union's Horizon 2020 research and innovation programme - H2020-EU.1.3.1.

Partners: Technion Israel Institute of TechnologyUniversity of CambridgeTechnische University BerlinUniversity College DublinUniversity College LondonTrimble OyFundacion CARTIFLocLab Consulting GmbH

Laing O’Rourke Centre involvement: Deputy Coordinator Dr Ioannis Brilakis

Dates: March 2020 – February 2024