Once embedded in the asphalt, the sensor fabric's job is to provide continuous measurements, allowing for conclusions regarding the internal condition of the asphalt base layer.
Scientists have developed a smart fabric embedded with sensors that can monitor the hidden health of asphalt roads in real time, in a breakthrough that could make resurfacing more sustainable, cost-effective, and less disruptive for drivers.
To design the innovative solution, the team of researchers from the Fraunhofer Institute for Wood Research, at the Wilhelm-Klauditz-Institut (WKI) in Germany, teamed up with experts in the SenAD2 project.
The solution is a bio-based fabric reinforced with conductive sensor wires that is embedded directly into the asphalt. Once installed, it measures strain and stress within the base layer, with AI algorithms analyzing the data to provide real-time insights into road health.
According to the institute, these changes alter the fabric’s electrical resistance, providing a constant flow of data about the road’s condition. They hope this interaction between the sensors and AI will help assess the condition of road structures in real time.
Road maintenance has long relied on visible surface wear or destructive core drilling to assess deeper damage. While cracks and surface defects caused by traffic and environmental stress are easy to spot, detecting micro-cracks and damage in the lower layers still requires drilling and extracting core samples.
This, in turn, can lead to costly and inefficient repairs that not only disrupt traffic flow but also shorten the lifespan of the roadway. Now, in a bid to address the issue, the researchers created a smart measurement and analysis system that can monitor the condition of the asphalt base layer nondestructively over a large area.
Industrial zone tests: As the first step, the sensor fabric is installed across the full width of the roadbed.Credit: Fraunhofer WKI
“Our goal is to be able to plan over a longer period of time, to continuously monitor changes in the condition of the road and, on that basis, to establish forecasts and incorporate them into maintenance management activities,” Christina Haxter, a research scientist at Fraunhofer WKI, revealed.
According to Haxter, the system provides continuous insights and improves the planners’ ability to decide when and where resurfacing is needed. The team’s goal is to track and predict how asphalt roads degrade. “This won’t make the roads last longer, but it will improve efforts to monitor their condition,” she elaborated.
The novel sensor fabric is lightweight and made from flax fibers, a natural, renewable material which is inexpensive to make. It is interwoven with ultra-thin conductive wires less than a millimeter in diameter.
The material is integrated directly into the natural fiber fabric during the weaving process, making it highly resistant to slippage or displacement. The use of thick, heavy yarns and wide spacing further stabilizes the material.
“The fabric has to be designed in such a way that there is no breakdown of the structure in the asphalt,” Haxter explained. “The sensors must also not be damaged either during the weaving process or when the fabric is inserted into the roadbed.”
Haxter further revealed that the fabric is produced to withstand the weight of trucks and road pavers during construction work. Made on a double rapier loom at Fraunhofer WKI, it can be manufactured in widths of 19 inches (50 centimeters) and at any desired length, making it scalable for real-world applications.
Road pavers cover the sensor fabric with asphalt.Credit: Fraunhofer WKI
“The fabric is designed to withstand the rigors of installation and environmental conditions, as our initial tests have shown,” Haxter concluded in a press release. Once embedded, the sensors feed their data to a roadside measurement unit, which stores and transmits the information for analysis.
Then, AI-powered software interprets the data to identify damage patterns and estimate how the road will degrade over time. The system also includes a digital dashboard, which makes the insights accessible not just to road agencies but also to businesses, communities, and road users affected by maintenance schedules.
After successful lab-based feasibility tests, the system is now being trialed on a flat road segment in an industrial zone. The sensor fabric spans the full width of the roadbed, with measurement nodes recording resistance changes as vehicles pass over.
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