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Laing O'Rourke Centre for Construction Engineering and Technology

 
Digital Engineering

Advances in technology are already transforming the way information is used by the supply chain at all stages of the construction process.

Digital Engineering encompasses a vast and growing area of study including everything from on-site automation and machine learning to exploring the use of satellite data for infrastructure monitoring.

 

Project: Application of satellite technology in infrastructure monitoring

This project takes forward the outcomes of a Laing O’Rourke Centre PhD student’s work.  Sakthy Selvakumaran’s thesis looks at utilising INSAR (radar) satellite imagery for monitoring the displacement of critical infrastructure and identifying displacements that could be precursors to failure. [Further information]  

Sponsors and Partners: Sakthy was awarded the Isaac Newton Trust/Newnham College Research Fellowship in Engineering, which she will use to establish and lead a growing research group in this field. There is considerable interest from government and industry partners in this project. Plans for this emerging group are developing with various collaborators, including The Centre for Digital Built Britain (CDBB) and Centre for Smart Infrastructure and Construction (CSIC).

Laing O’Rourke Centre involvement: Academic Supervisor Prof. Cam Middleton, Researcher Sakthy Selvakumaran.

Dates: October 2019 – ongoing

 

Project: Artificial Intelligence Optimised Pathways for Schedule Execution

The project seeks to develop a novel automated 'schedule learning platform' that applies data science and machine learning to thousands of previous project schedules, offering a unique scalable solution for improved certainty and confidence in project planning for future projects. The solution is based on thousands of previous construction projects, allowing the platform to learn across projects what was planned to happen and what actually happened, thus reducing the effect of human bias, subjectivity and inaccuracy. Schedule data is analysed, similar tasks and relationships are automatically grouped, with patterns drawn using Artificial Intelligence, enabling the platform to predict the most likely outcome for every task and provide optimal paths/recommendations to mitigate risks/delays. [Further information] 

Sponsor: Innovate UK

Partners: nPlan, Kier

Laing O’Rourke Centre involvement: Investigator Dr Ioannis Brilakis, Research Associates Sally Xie and Ying Hong

Dates: March 2019 - February 2021

 

Project: Interactive Point Cloud and Image Data Generation in Infrastructure Scenes

All construction trades and inspectors need spatial and visual data to operate. However, extracting up to thousands of measurements and creating meaningful registered data sets in a single work shift translates to a sizable portion of work time dedicated to measuring and processing instead of direct work. The research is mainly focused on increasing the efficiency of geometry and visual data collection by devising a system that tackles the challenges in data collection and post-processing through a combination of high-resolution DSLR cameras and a hand held laser scanner.

Construction operatives and inspectors could benefit significantly from laser-scanner-quality data in terms of resolution and accuracy, with the mobility and reachability of hand held devices and the ability to operate outdoors reliably and from long distances.

Sponsors and Partners: BP, Laing O’Rourke, Topcon, GeoSLAM, Trimble

Laing O’Rourke Centre involvement: Principal Investigator Dr Ioannis Brilakis, PhD student Maciej Trzeciak

Dates: October 2017 – September 2021