Fugro Roadware helps bridge the pavement knowledge gap with iVision

Fugro Roadware Inc. says its iVision software help road engineers understand how a section behaves over time. Users of the software specify the exact road location they would like to view using co-ordinate or other identifying information and simultaneously call up an array of road data, including maps, pavement images, driving videologs, and collected pavement management and condition data.

Road engineers are often frustrated by the gap between the hard data that describes the condition of a road surface and the ability of decision-makers to fully understand it.

Fugro Roadware Inc., a pavement management technology and data collection specialist based in Mississauga, aims to change all that with the recent release of its iVision web application package.

Users of the software specify the exact road location they would like to view using co-ordinate or other identifying information and simultaneously call up an array of road data, including maps, pavement images, driving videologs, and collected pavement management and condition data.

The road data is collected by Fugro Roadware’s familiar Automatic Road Analyzer (ARAN) vehicles, which the company first launched in 1985. The vehicles are either contracted by clients to perform road analysis on specific roads, or sold outright to clients along with a compatible software suite.

“The iVision software basically gives a lot more features to road and highway engineers to help decision-makers to understand how the road is performing over time, and what might be required to effectively treat any deficiencies,” says Michael Nieminen, director of technology development with Fugro Roadware. “You could send a link to a city councillor or city engineer, for example, and you could show them road conditions at the exact location you’re discussing. It also presents the data and images in such a way that you don’t need to be a pavement expert to understand what’s happening to the road surface.”

Although it can be installed on a client’s server, the iVision package is typically hosted on Fugro Roadware’s own servers and offered on a subscription basis to users, who access it as a web-based application. Subscription prices are based on whether the user signs on to the iVision Standard or Professional version. However, sharing road information with decision-makers does not add to the cost of the service.

The iVision software is based on the company’s proprietary Vision software, once used exclusively inside the company to analyze road data, but also recently released to the public closely on the heels of iVision.

“The difference between the two software packages is that Vision is a desktop-based software designed to allow you to process and work with the data, while iVision is designed to get the data out and share it with others,” says Nieminen.

Vision additionally gives engineers detailed information on road conditions, including road images displayed at one millimetre resolution, and three-dimensional pavement modeling.

“It offers a lot more features that will help road experts to understand how the road is holding up,” says Nieminen. “For example, it also reports on pavement distress by incorporating our WiseCrax automated crack detection software, which can provide colour-coded overlays on road surface images that identify crack locations by severity and type of crack.”

The software is also expandable, offering new features as the mobile ARAN scanning system becomes increasingly sophisticated.

“Our ARAN vehicles now also offer ground-penetrating radar, so instead of just reporting information on the fresh, new coat of asphalt on top, Vision can display the thickness and quality of each road layer down to the sub-base,” says Nieminen.

Vision can now also offer some suggestions on how road problems can best be remediated.

“We’re in the beginning stages of this sort of functionality, offering some fairly high -level suggestions on what’s wrong with the road, and what might be done about it, based on the available data,” says Nieminen. “With future releases of the program we hope to build on that ability.”