Telematics systems have the potential to influence driver behaviour positively, but fleet managers must sift through a huge amount of data to gain the actionable insights required. Steve Thomas from Inseego UK explains how the latest AI tools transform data analysis to enable fleet managers to better engage with and manage their drivers.
Telematics is ultimately about altering behaviour, but it has been the responsibility of the fleet manager to use performance data to engage with drivers directly,’ explains Steve Thomas from Inseego UK. ‘Historically, the telematics system has provided the tools for the fleet manager to support better driver communication, collaboration, and decision making, but all too often, the amount of data generated becomes overwhelming.’
From a fleet manager’s perspective, one of the biggest issues is the amount of data they must contend with daily from multiple systems and hardware. Overstretched fleet management teams often lack the time and resources to analyse this data. The latest telematics innovation, increasingly using AI-powered tools and processes, has the potential to transform how critical data is analysed, providing much-needed support to fleet managers.
Steve explains that these tools can increasingly be used to interrogate a wide range of data and video sources – behaviour, incidents, near misses, fuel usage, speed limits, location, and weather conditions – to create a holistic view of driver performance. This AI-powered analysis will enable the telematics system to understand where issues exist and take the appropriate steps to resolve these exceptions.
‘By combining multiple data sets that would be impossible to analyse manually, a fleet manager can create a true picture of fleet risk and pinpoint driver behaviour that requires attention. Someone speeding in the rain outside a school is clearly a higher risk than someone marginally over the speed limit in dry conditions on a motorway. However, most current systems would not differentiate, making it harder to prioritise interventions.’
He uses vehicle cameras as an example. ‘These typically upload video clips based on g-force events, but they are often triggered by false positive events such as harsh driving, potholes and speed humps. For a fleet of 50 vehicles, if each generates four clips per day, the fleet manager would have 1,000 videos to watch weekly, which is not workable. This is not just about having the time to view footage, but also being able to react quickly to situations that need immediate attention, both from a duty of care and insurance perspective.’
He explains that using post-event machine vision, the new video telematics software can view the video clips and flag those needing attention. This means a fleet manager can quickly focus on collisions or incidents involving a vulnerable road user. ‘AI technology of this kind has already been shown to reduce the number of clips needing review by as much as 99%, leaving just a handful that can be checked in a matter of minutes.’
Steve also believes that driver communication and management will increasingly be influenced by AI, with greater levels of automation as a result. ‘This is happening already to a certain extent, but we will see the technology rapidly evolve to the point where the telematics system can communicate with the drivers directly, which will massively reduce the burden on the fleet manager.’
There are already active examples around driver behaviour monitoring and education, with targeted training developments that provide engagement and coaching triggered by specific recurring behaviour. Creating bespoke programmes – with automated safety messages, performance reports and training modules – can address individual issues, change driver attitudes, and mitigate fleet risk.
‘Moving forward, we will start seeing the technology handle many aspects of fleet management, including training, compliance, vehicle usage, and working hours to take on much of the hard work,’ says Steve. ‘Many driver, vehicle and fleet processes will soon move from human intervention to automatic system management, leaving the fleet manager to deal with the 2-3% requiring their attention. For the rest, they can oversee using reporting dashboards that intelligently measure ongoing performance.’
Of course, there will be those – both drivers and fleet managers – who view AI with suspicion. Similar concerns have been raised about other fleet systems, such as vehicle tracking and video telematics, but the adoption of these technologies is increasingly widespread and accepted. Steve believes this will be much the same for AI as a greater understanding of its value and potential becomes clear.
‘AI-powered telematics has a vital role in driver management, providing valuable data and insights that will make it much easier to spot and correct the most serious issues. It will transform how critical data is analysed, enabling fleets to implement the robust and automated processes needed to improve driver safety, compliance, productivity and efficiency.’
