As the pressing need to inspect and repair aging infrastructure has grown, so have the challenges in doing so. Bridges, highways, dams and other infrastructure are exposed to elements from all sides, and defects can be difficult or even dangerous to reach.
As a result, minor defects, initially inconspicuous or even invisible to the human eye, can result in sometimes life-threatening consequences over the long term - the recent collapse of the Fern Hollow Bridge being quite a sobering reminder of what can go wrong.
These issues pose major financial and security challenges for businesses and governments as the detection and prevention of corrosion and damage is time-consuming and prone to error.
After more than three years of development, the German company Twinsity has launched TWINSPECT, a software solution that fully digitizes the drone inspection process making inspections safer, easier and more cost-effective. While drones have revolutionized the inspection of infrastructure and buildings, they generate large amounts of unstructured data that for the most part must be manually processed to create usable information.
Twinsity was founded by the father and son team of Uwe and Fabien Chalas, two software architects. By creating a 3D “Digital Twin” of a structure, they have created a workflow that enables the inspection process to become faster and more collaborative, says Fabien.
“Our platform is like a professional ´Google Earth for inspections'. We saw the opportunity and necessity to create an interactive and collaborative platform for accessing and analyzing drone data for the inspection teams and asset owners.”
The cloud-based software system behind TWINSPECT identifies and analyzes even the smallest defective areas thanks to the real-time visualization of objects. The software platform architecture ensures efficient processing of the inspection data. As an integral part of the inspection process, the platform also guarantees access for all those involved.
In addition, the software automates the detection of existing damage and consequently minimizes the risk and burden on people and materials. In the field of predictive maintenance, buildings can be checked regularly and quickly in a more cost-efficient manner and the structure can be evaluated in real-time to identify any damage and anomalies as early as possible.
“The infrastructure lifecycle management system is available to reliably check and track the development of the corresponding object over a certain period of time," says Uwe Chalas, Managing Director of Twinsity GmbH.
Machine learning technologies enables the continuous optimization of TWINSPECT's detection and analysis system in terms of precision and speed. Precision measurements down to the millimeter are taken directly in the 3D model, resulting in an automatically generated inspection report with visual documentation and trend analysis.
“With TWINSPECT, Twinsity offers drone service providers a completely unique way to finally make their inspection data efficiently available to their clients. Engineering firms and asset owners get an intuitive communication and analysis platform for much more cost-efficient, fast, accurate and safe damage documentation and inspection of their infrastructure and assets.”, says Fabien Chalas.
