Northumbria University has teamed up with BuildStream, BIM Academy and Costain to develop a solution to address the productivity challenges facing equipment on construction sites.
The tie-up was facilitated by an Innovate UK collaborative R&D grant.
The team is employing BIM and IoT technologies and machine learning techniques to improve the productivity of equipment. Earlier work by the consortium at the HS2 project confirmed demand for systems looking at equipment fleet management (such as estimation/selection, deployment, coordination, and visualisation).
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The project is now in its second quarter and is gearing up for hardware installation on site to generate datasets that are more granular than those currently available within the industry. Other datasets, including legacy data, programmes and models, are also being used as part of the proposed solution.
Northumbria University is responsible for information baselining and development of machine learning algorithms and their integration within the solution. The Northumbria team has started the implementation of these algorithms using the datasets to measure equipment productivity. The team at Northumbria includes Dr Mohamad Kassem (project lead); Dr Kay Rogage (co-project lead), and Dr James Huntingdon (research fellow).
Dr Kassem, who is also associate professor in the Mechanical and Engineering Department at Northumbria University, said: “It is exciting to see that in the construction sector we have the means, using machine learning techniques, to automatically detect equipment operations and measure their productivity, a historically major blind spot in the construction sector productivity.”
Dr Huntingdon added: “There are significant challenges in managing data being generated within construction. One example is the inconsistency in data and how it is captured by existing telematics. By creating streamlined IoT devices and data pipelines managed by cloud-computing this project is meeting challenges set out by the Association of Equipment Management Professionals (AEMP2). Automating data and inferring knowledge from this data using artificial intelligence is a major leap forward in unlocking efficiencies within this sector.
BIM Academy has been exploring Synchro Pro and Site project management software, building a 4D model and looking at how live data captured from sensor equipment can be utilised and fed into the model, with a focus on plant and equipment. Research is being carried out on exploring the possibility of creating plug-ins to automate and allow for this process to happen. Conversations with Synchro on access to its APIs (application program interfaces) are ongoing.
Dr Graham Kelly, director at BIM Academy, said: “Working on this project gives BIM Academy a fantastic opportunity to push the boundaries of current 4D modelling to add real value with regards construction site logistics. We are hoping that the link between equipment data and 4D models will not only support improvements to productivity and planning, but also further improve H&S and sustainability on site.”
Terrence Clarke, project lead at BuildStream, said: “At BuildStream we are setting out to transform the productivity of heavy equipment operations across the global construction industry. Whilst in recent years we have seen the mass digitisation of project management and design tools, the on-site operation of heavy equipment remains an untapped market and huge opportunity. By capturing the right data and providing detailed analytics to project teams in a collaborative environment, we are helping contractors get the job done safely, on time and on budget.”
Image: Mrtwister/Dreamstime.com
