The way we design, build, and operate infrastructure must evolve rapidly to meet new global demand, support renewable energy goals, and more. Technology is the enabler of a more strategic approach to this.
An abundance of data is generated from design through to the operations stage, which can be leveraged as a source of intelligence, but only if used in a workable format. Julien Moutte, CTO at Bentley Systems delved into the definition of intelligent infrastructure, and how the company leverages data from IT, operational technology (OT), and engineering technology (ET). Bentley Systems compiles these three data sources in what it calls ‘intelligent infrastructure.
Moutte explains how important ET data is—such as 3D digital models and CAD—and how it can be leveraged by engineers. “It's more important than ever to make this infrastructure intelligence available to engineers so that they can do their best work. Because in our sector infrastructure is under a lot of pressure right now due to project backlogs, talent shortages, and sustainability requirements.”
Creating a digital twin of infrastructure affords engineers the ability to experiment with real-life developments in a simulated environment, which enables more predictive activity to mitigate future issues. In this process, artificial intelligence can play a key role in building the environment in the digital realm while machine learning can be implemented to continuously predict real-life actions and their impacts.
“I think it's important for us to understand that AI and ML are already delivering considerable value to the infrastructure sectors. A lot of our accounts and users use AI today in their projects, whether they use it for something like computer vision to be able to assess the state of a bridge or a dam,” says Moutte.
“Also, maybe to use AI to automate a lot of tedious tasks like looking at CAD drawings—thousands and thousands of CAD drawings and identifying the crosswalks—the shoulder widths and the lanes inside those designs to create that digital twin is something that is already happening today.”
Moutte said Bentley Systems is seeking to address concerns of data usage and the reliability of AI—particularly in light of conversations where generative AI is at the forefront. Assurance is key to not only onboarding customers with AI-driven solutions, but also ensuring a thorough approach to infrastructure development, which means focusing on the transparent use of AI. The company has committed to ensuring its AI solutions respect intellectual property and data privacy rights.
Moutte explains that, while AI has huge potential for utilising data to create infrastructure designs, Bentley Systems emphasises the need for AI to be a digital companion for infrastructure design, not a replacement for engineers.
“We believe this is an approach that is going to help our users understand how the data is being used, have control, but also make the best use of past data.”
“Our tools already understand the rules of the physical world, the constraints of engineering, and we want to make sure that AI is working as an assistant to the designer and engineers and of our tools so that they can enforce those engineering rules and make sure we create safe designs.”
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