Construction projects—specifically infrastructure projects—are becoming more complex than ever before. As Julien Moutte, CTO, Bentley Systems, recently told me on The Peggy Smedley Show, the demand on infrastructure has never been so high for many reasons, which he explains on the podcast. Here at Constructech, we have been talking about failing infrastructure around the world and in the United States, the need for greater resiliency and sustainability, and the need for greater security of our infrastructure systems.
With the help of technology, there are opportunities to build infrastructure that is modern, resilient, and sustainable. However, building these projects is easier said than done. Enter digital twins and AI (artificial intelligence).
Gen AI has truly seen an uptick in recent years due to several factors, but as we all know, artificial intelligence isn’t necessarily new. It has been around for decades. Moutte says it has been researched as early as the 1960s, but what is true is in the last two years AI has exploded. He explains the tipping point was the size of the model, the rise of ChatGPT, and the fact that it is finally able to have a conversation with humans.
“We are seeing our sector transforming progressively and more and more rapidly over the last two-or-three years as well where we see that we are entering the era of the digital twin for infrastructure and construction,” he says. “We can see that the engineering tools—and Bentley has created a lot of those engineering tools—are being used more and more by the engineering firms and the construction firms and we see that a lot of those firms are implementing digital workflows.”
Collecting and gathering data is what is key here. Moutte tells me the data that is produced around the lifecycle of the infrastructure asset is gold and it must be managed very carefully.
“AI, by definition, is not very useful if you don’t have data,” he explains. “You need to have good, credited data because with AI, like with everything else, you get garbage in, garbage out. So, you better make sure you have good data coming into the AI model because otherwise they are not going to be proven very useful for you.”
The methods and technology tools continue to evolve as well. Moutte points to a few examples of new technology that is enabling the flow of data coming from the field. Some examples include cameras mounted on the helmets of the field workers, LiDAR scanners that are attached to the cranes that are scanning the whole construction jobsite, and automated machinery, just to name a few.
He explains one of the best ways to ensure data is being managed very carefully is to create a digital twin—a digital replica of the physical infrastructure asset, which is both realistic enough for the outcomes and provides the latest data to make sure workers are making the right decisions.
We are seeing the rise of digital twins in a host of industries—but particularly on infrastructure projects. Fortune Business Insights suggests the global digital twin market is anticipated to grow 39.8% from 2024 to 2032. The opportunities for it are huge too. Digital twins can help with safety, productivity, collaboration, communication, resiliency, sustainability, and carbon calculation, ultimately leading to construction project cost savings.
As we continue to see the rise of AI, we must consider the value and the role of the data. For infrastructure projects, digital twins will be critical to ensure that data is managed well.
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