Our AI-based BATT Vision smart pavement monitoring provides over-the-top accuracy in pavement condition assessments

AI-based, BATT Vision—powered by Tiger Eye Engineering—is a high-tech smart pavement monitoring service that combines artificial intelligence with a streamlined data collection process, data analytics, and data visualization to achieve a high level of accuracy and consistency in assessing the condition of asphalt pavements.

BATT Vision utilizes high-resolution, 360-degree cameras, along with action cameras, a GPS unit, and accelerometers to robustly capture pavement conditions. GPS-labeled video frames are analyzed by proprietary software to extract images at specified intervals, remove duplication, and sample the pavement network continuously. The result is a far superior analysis than commonly used data collection vehicles can produce, and a more consistent analysis than subjectively based, feet-on-the-ground surveys.

The system provides reports that allow engineers, agencies, and owners to fully understand their pavements.  It generates performance condition index (PCI) data that can be used to evaluate and fine-tune pavement treatment decisions over the life of the pavement.  The report provides access to an online data visualization tool that includes distress photos and graphs.

In contrast to older analysis methods, BATT Vision utilizes a suite of software that applies machine learning and deep learning techniques for detecting distress in both flexible and rigid pavements. The BATT Team can then use the system’s algorithms to detect the type, extent and severity of the distresses and calculate a PCI using standardized equations. On a scale from 0 to 100, a PCI value of 100 would signify a superior pavement condition.

Heat maps of pavement conditions or other user-selected data can be holistically viewed, and the statistics of the distresses can be categorized based on the city or county area and can be filtered by pavement type or classification, traffic level, and more. Corresponding camera images and video replays are a simple click to access and can be filtered to superimpose ML-assessed pavement distresses and locations. Multiple user accounts to access the data visualization platform are available on request.

I predict BATT Vision will set a new standard in pavement analysis accuracy, allowing our clients to make more cost-effective and consistent decisions as they manage their network of urban or rural pavements. This technology is also extremely valuable in assisting BATT to evaluate new products and enabling those products to move from lab to field successfully.

For more information on BATT Vision, contact the BATT Lab via the Get In Touch button at the bottom of this page.