A new AI-powered video analysis solution that can transform commercial fleet safety through more efficient risk management is now available from VisionTrack.

VisionTrack says NARA will revolutionise how vehicle camera footage is assessed

It’s dubbed NARA (Notification, Analysis and Risk Assessment) and uses computer vision models with sensor fusion to assess footage of driving events, near misses and collisions. This reduces the time taken to review events, ensuring the review process is manageable and timely, while eliminating human availability or error.

VisionTrack says it will revolutionise how vehicle camera footage is assessed and help vehicle operators to dramatically reduce road deaths and injuries.

Richard Kent, president of global sales at the AI video telematics and connected fleet data specialist, said: “Our cloud-based NARA software is a true game changer in the world of video telematics as it will help save time, costs and most importantly lives, by providing proactive risk intervention and accurate incident validation.

“NARA proactively removes false positives and monitors driver behaviour, without the need for human involvement. With traditional video telematics solutions, commercial fleets can be experiencing hundreds of triggered daily events, so this will enable them to deliver more efficient working, whilst not compromising on road safety.”

Importantly for fleets, it’s ‘device-agnostic’ so can be integrated with existing connected camera technology – whether VisionTrack or third-party hardware – adding another layer of analysis to AI vehicle cameras, which the company says are often limited by the processing capacity of the device.

It’s already been tested with a 1,100-strong logistics fleet, which was generating on average 2,000 priority videos a week. These would typically take someone over eight hours to review but was slashed to just minutes with NARA. As a result, the company is now targeting more efficient risk management, whilst supporting their road safety strategy.

The technology’s advanced object recognition makes use of deep learning algorithms to automatically identify different types of vehicles, cyclists and pedestrians. It’s said to have incredibly high accuracy levels, making it able to distinguish between collisions, near misses and false positives that can be generated by harsh driving, potholes or speed humps.

The software will also include Occupant Safety Rating that uses a range of parameters to calculate the percentage probability of injury and immediately identify if a driver needs assistance.

“As a true advocate of road safety, having already pledged our support to global initiative Vision Zero, we are passionate about helping the industry achieve its target of eliminating all traffic fatalities. Our vision is to create a world where all road-users are kept safe from harm, so we are embracing the latest advances in machine learning and computer vision to further enhance our industry-leading IoT platform, Autonomise.ai, and AI video telematics solutions,” concluded Kent.