The maintenance of urban infrastructure — including railroad networks, bridges, pipelines, and power transmission towers — has to be carried out regularly to keep the infrastructure alive and competitive. Using modern technologies such as machine learning, wireless sensors, and mobile apps, to remotely examine and monitor this infrastructure, could eliminate the need for regular examination, thus saving money and time for civil engineers and reducing the risk associated with working on construction sites.
We all are used to working with smart devices, including iPads, laptops, and mobile phones. Imagine if we used these advanced technologies to perform high-tech civil and engineering work. Engineers and developers are already working on “digital twins” — the 3D replica of a physical entity using IoT — to inspect infrastructure performance under several service conditions and make smart decisions accordingly.
The digital replica is the twin of the in-source infrastructure. Wireless sensors are used for two-way communication between the physical entity and the computer. This is very useful for contract engineers who need to carry out regular daily inspections to monitor the performance of infrastructure. They make intelligent infrastructure decisions about which structural elements need to be replaced or worked upon, to ensure the safety of the infrastructure.
The concept of developing digital twins is still in the nascent phases for civil and infrastructure engineers. Digital twins are being developed in the Netherlands for operation at the Port of Rotterdam. Furthermore, a team of engineers from the Norwegian University of Science and Technology is building a digital model of an operating crane.
Using Digital Twins to Improve Infrastructure Maintenance in Australia
Now, a team of researchers from the School of Engineering at RMIT in Australia are working on creating digital twins for use in smart infrastructure maintenance across the country. The aim of the researchers is on bridge and port infrastructure. But soon they plan to use the developed models for wastewater pipelines, offshore platforms, wind turbines, railways, LNG, power transmission towers, and oil and gas pipelines.
The team has also built a cloud-based asset management platform — Central Asset Management System (CAMS) — that uses discrete condition ratings given to engineering elements through examinations. These ratings can be used to further build predictive models to support decision-making and proactive planning on civil infrastructure. CAMS is used by public-private partnership clients for the modeling of life-cycle of buildings.
RMIT researchers are working on the integration of live monitoring of infrastructure for the advancement of CAMS towards the development of digital twins. They have made available the system for trial by any interested infrastructure owners.
The development of the model represents a significant step towards smart cities, thereby helping create a safer and healthier community.