The Government of Victoria in Australia is providing funds to improve bridge maintenance with fiber-optic sensors to better ascertain structural strain, thermal response, bending, loads and vibration. The government’s $39 million investment in the tiny sensors is part of a joint venture with Xerox to develop the technology for the industrial internet of things.



The Victorian Government of Australia has committed AU$50 million to deploy tiny fibre optic sensors onto bridges across the state for early detection and prediction of problems, thus preventing costly repairs and helping bridge operators to efficiently manage maintenance budgets.

“This will help to detect problems earlier, reduce delays caused by road closures for manual inspections and repairs, and help to find problems more quickly and accurately in the case of bridge strikes or other unexpected events,” said Victorian Minister for Transport Infrastructure Jacinta Allan.

The state government has partnered with technology vendor Xerox on a joint venture named Eloque to commercialise the new technology that will remotely monitor the structural health of bridges.

“The technology has already been deployed on 7 bridges in Victoria and will be progressively deployed on priority bridges, particularly those that regularly deal with heavy loads and are at the most risk of deterioration. This is solving a major pain point for customers and allowing them to better manage their assets,” said VicTrack chief executive Campbell Rose AM, who has taken the role of CEO of Eloque to support the company through its early establishment.

The Eloque solution is an Industrial Internet of Things (IIoT) technology, that accurately measures and estimates structural strain, thermal response, bending, loads, vibration on bridges. Advanced analytics are then used to evaluate the sensors’ data and deliver insights directly to the bridge owners and operators in real time, to monitor whether a bridge is being over or underutilised, has structural problems or damage that needs repair.