Through digitalization of the building and construction sector, we will be able to build safer, faster and more sustainable. The digital transformation will also enable new business models and result in a higher return on investment.
The research topic of digitalization (within the built environment) encloses four subtopics:
- Digital twins
- Artificial Intelligence
- Augmented & Mixed Reality
Digital twins are virtual representations of an object. Digital twinning is useful in the full life cycle of buildings, above and underground infrastructure, and in urban areas. A digital twin can provide real-time data when linked to sensors in the physical environment. In this way, the data can be used for:
- Analyzing design and construction processes (e.g. for construction site planning and real-time logistics),
- Optimizing maintenance and operation (e.g. tunnel technical installations, HVAC installations, structural health, solar shading),
- Enabling new developments (e.g. based on emergent patterns or digital testing of new concepts).
The challenges initially revolve around developing digital twins for lifecycle management, developing 'as-built models' and linking with BIM, GIS, secure, privacy-conscious data storage (and further use), linking with monitoring techniques and developing of usage applications.
The digital twins research program focuses on developing methods for registering geometric and usage data (with sensors) of objects and construction processes, in user-friendly tools and models. This includes standardization. The methods, tools and models can be used for:
- Smart construction sites (Edge AI, progress monitoring)
- Simulations and Predictive Digital Twins
- Smart Buildings
Robotics uses (semi) autonomous machines that take over tasks that are too risky, repetitive, difficult or inefficient for humans. Because machines have become more commonly available and flexible in installation and use, they can often produce cheaper than a human being and they play a role in production halls. However, the integration of robotics and mechanics on the (inherently) dynamic construction site remains a challenge. Machines such as 3D concrete printers, steel welders, cranes, autonomous vehicles (AV), drones and excavators can be controlled (semi-automatically) from control rooms to automate the construction site.
The robotics research program line focuses on the development and testing of robotic machines in production halls and on the construction site. Prototypes are developed for different contained and secured construction processes (e.g. to support digging, lifting operations, monitoring of progress on the construction site or for assembly by welding and 3D printing), followed by implementation studies in more unruly environments. In this, we are focusing on four topics within the building and construction sector:
- Smart Buildings & Infrastructure
- Industrialization & Smart Production Systems
- Robots and cobots on the construction site
- Maintenance, monitoring, and inspection
Artificial Intelligence (AI)
Artificial Intelligence (AI) uses optimization techniques and large data sets. Learning algorithms can, for example, develop prediction models for building simulations, analyze design models and construction processes, find anomalies and errors in (building) models, and control self-learning robots. In combination with the above, it provides a strong basis for decision support in all kinds of places in the built environment. The challenge is to develop reliable, insightful and useful AI algorithms that minimally support and in some cases replace human thinking and human actions in terms of performance, reliability and logic.
The AI research program focuses on developing methods with which the reliability of existing data can be analyzed, with which design and planning can be automated/optimized and with which machines become self-learning and safer. AI also takes place within the two program lines above, for example through a link between AI and hardware in the loop simulations (robotics), with which predictions are made about, for example, failure rates of infrastructure. The semantics and data handling in digital twin research of course also typically relies on AI techniques (knowledge graphs, model-based prediction). It is important to make a direct link with monitoring the actual performance in practice, which can ultimately lead to acceptable risks in predictions.
The AI program focuses on three topics within the building and construction sector:
- Generative design and optimization in design and execution
- Combining model-driven (BIM) and data-driven (ML, AI) design methods
- Object Recognition, Error Detection, Object Recognition (e.g. for structural health monitoring)
Mixed Reality (AR-VR-MR)
Virtual Reality, Augmented Reality and Mixed Reality integrate real-time virtual data with a camera image of reality. This supports an intuitive way of visualizing key elements in design, execution, management, maintenance and inspection, but also provides the basis for training and process improvement. VR, AR and MR technologies have three basic functions in construction: visualization, information retrieval and interaction. They can be used to experience and maintain buildings, machines and robots remotely, or for training and process improvements in so-called feedback support systems.
The VR – AR – MR research program focuses on three topics within the building and construction sector:
- Education and training
- Lifecycle Management
- Design and execution