Digital twins are making waves in industries across the globe. Their benefits are plentiful, and the construction industry wants to take advantage of all they have to offer.
But adopting any new technology comes with bumps in the road, and construction sites don’t always have the means to support cutting-edge digital technologies.
A new ASCE book, Digital Twins in Construction and the Built Environment, takes a comprehensive look into digital twins, the challenges the construction industry faces with their implementation, and the benefits they offer the field.
The ASCE Global Center for Excellence in Computing Committee, particularly Houtan Jebelli, Ph.D., EIT, A.M.ASCE; Somayeh Asadi, Ph.D., A.M.ASCE; Ivan Mutis, Ph. D., A.M.ASCE; Rui Liu, Ph.D., P.E., M.ASCE; and Jack Cheng, Ph.D., A.M.ASCE, who took on the task of creating this book. Civil Engineering Source recently spoke with Jebelli, who chairs the committee, about the use of digital twins in construction and how the book aims to support their implementation in the industry.
Civil Engineering Source: How are digital twins changing the construction industry?
Houtan Jebelli: Digital twins are not a new concept . They have been used in so many different industries, from manufacturing to other field industries. But in construction, it's a relatively new term.
The general idea of digital twins is the integration of real-time data from sensors that are embedded in structures or connected to workers or other equipment.
Traditionally, we can find some digital twin terms in the literature that are connected to building information modeling or other simulation approaches. Those are great areas, but they cannot be categorized as digital twins under the novel definition because the real-time component is missing.
If we consider the construction industry nowadays, we can think of digital twins in the areas of structure health monitoring and predictive maintenance systems.
My group works on a digital twin focused on safety and health monitoring using wearable voice sensors and signals to understand workers’ health and safety in near real-time.
To support this work, I’m fortunate to lead several projects funded by the National Science Foundation and the NIOSH-CDC program focused on advancing real-time data collection and improving worker safety and health.
Another example is digital twin concepts when it comes to human-robot collaboration. These days, we have robots that are emerging in the field. But it is really important to ensure the safety and productivity of workers when they are working with those robots. For safety monitoring, the digital twin could play an important role in that.
But again, this is an emerging field, and we should expect to see the application of digital twins in several aspects of construction and the civil engineering industry in general.
Source: What inspired the creation of this publication?
Jebelli: The idea emerged from the increasing momentum around digital twin technologies in the AEC industry, particularly their integration with the Internet of Things, artificial intelligence, and building information modeling. We noticed a gap in comprehensive resources that both practitioners and researchers could rely on, so the goal was to bring together leading experts to produce a timely, authoritative reference that bridges theory and application.
By definition, digital twins should reflect the real-time or near real-time status of physical aspects, like the structure monitoring worker safety or whichever component of interest. Traditionally, we can see in our field that there are works that are refined to digital twins but are missing the real-time component.
We were inspired to understand the need and the current and future trends in the domain and pursue this. Our goal was to work on something that can benefit the industry as a whole.
We had contributors from Europe, New Zealand, Asia, and the U.S. That was an important aspect for us because we wanted to address the global challenge and provide an opportunity for collaborators around the world to share their thoughts on this important topic.
Source: What did the process of creating this publication look like?
Jebelli: It was a highly collaborative effort involving contributors from academia and industry. We curated chapters to reflect both foundational knowledge and cutting-edge applications. The process involved regular coordination with authors, peer reviewers, and the editorial team to ensure the content remained rigorous, relevant, and accessible.
I serve as a chair of the ASCE Global Center for Excellence in Computing Committee, and one of our visions is to be able to reach whoever is interested in the advancement of computing, not only in the U.S. but across the world, with a focus on the civil engineering community. Digital twins was one of the topics we could navigate because people in different countries are enhancing and exploring their potential advancement.
What motivated us to proceed with this book was the reach of digital twins. It can cover different aspects from structure health monitoring to predictive maintenance to human work collaboration, or even workers’ proactive safety and health monitoring.
After deciding on the topic, we submitted a detailed proposal to ASCE – which was reviewed by the Computing Executive Committee – and received great feedback.
We then reached out to the global computing community and received a handful of quality abstracts. Our selection process was very competitive.
After we received full submissions, we worked with our chapter contributors to address comments and improve their work. Then, we worked with ASCE to finalize the publication and edit what turned out to be a great book.
Source: What are the most significant benefits of digital twins? What are the biggest challenges?
Jebelli: Benefits include improved decision-making, enhanced asset performance, reduced maintenance costs, and better safety outcomes.
The major challenge we're facing is with technology. It is really important for digital twins to happen in near real-time. But that means the computational cost and time are also really important. Depending on the type of data you're collecting and the amount of computation that is involved, making that real-time prediction is not always feasible.
In construction sites where we don't have a supercomputer, we may not have 5G systems that can help us transfer the data, and that brings us some practical challenges to implement the system in the field.
Sometimes, you may have a really high-performance digital twin developing in our lab, because again, we can't control all those factors. We may use a GPU or supercomputer. We may use a 5G system to make the near real-time data acquisition and collection feasible. But in the field, you don't have that infrastructure most of the time.
That is the beauty of the work my group did. We tried to develop some algorithms that can reduce the computational power and cost of the systems.
Rather than proposing that everyone have a supercomputer at a construction site – which we understand is not feasible – we tried to develop some advanced algorithms that can fit our needs and that can make digital twin innovation feasible and beneficial for construction and other field-oriented industries.
Learn more about Digital Twins in Construction and the Built Environment.
